Data Scientist

Local Jobs Etsy in Data Scientist
  • United States, Brooklyn, NY 11201 View on Map
  • Post Date: July 3, 2020
  • Apply Before : August 2, 2020
  • Share:

Job Description

Company Description

As an Etsy employee, you can do the work you love, be yourself, and make an impact in the lives of millions. Our commitments to diversity and inclusion, team culture and the spaces where we work all reflect our mission to keep commerce human.

Job Description

Data scientists at Etsy use rigorous methods to generate insights that inform product, engineering, and business decisions across the company. We collaborate with partner teams through all stages of development: actively uncovering opportunity areas, crafting experiments to test hypotheses, analyzing the impact of our efforts, and highlighting takeaways.

Learning new skills and techniques is not only a requirement but a perk of the job! We are always looking for opportunities to grow. Our mission is to guide our partner teams with data and insights and tell the story of how we attract and retain our users — to teams, to senior management, and to the community.

We’re hiring partners for a few key Product teams, including the search experience and fulfillment teams. These groups are focused are enhancing their areas of the core shopping experience to connect more buyers with sellers offering just the items they need.

This role is located in Brooklyn, NY and is part of our Analytics and Strategic Finance team.


About the Role

  • Transform raw data into impactful analysis characterized by strong data governance/documentation, rigorous techniques, and actionable recommendations.
  • Partner with product, engineering, design teams; use behavioral and transactional data to shed light on our users and our product experience, identify areas for improvement, and drive decision-making.
  • Identify actionable metrics to understand the performance of products, develop reporting dashboards to track progress, and ingrain these metrics into teams’ day-to-day decision-making.
  • Lead experimentation, help teams set strong hypotheses, and deliver robust analysis of experiment results.
  • Continually evaluate and refine your technical toolkit; teach what you learn to the team.

Qualifications


About You

  • 2-3 years experience as an analyst or in a quantitative role in which you extracted meaning from big data sets with little engineering support.
  • Understand the principles of A/B testing, and love crafting and analyzing experiments.
  • Proficient in SQL and have familiarity with either R or Python. Bonus points for experience with the Hadoop ecosystem or additional scripting languages (Scala, PHP, Ruby, etc.).
  • Experience with Looker, Tableau, or other data visualization software a plus.
  • You look for ways to advance your technical skill set and to apply new methods to impactful questions.
  • You can communicate your insights verbally, visually, and in writing and care deeply about the quality and integrity of your work.
  • You want to play a key role on a cross-functional team.
  • You are passionate about subjects such as experimental design, data visualization, and statistical analysis techniques.

Additional Information

At Etsy, we believe that a diverse, equitable and inclusive workplace makes us a more relevant, more competitive, and more resilient company. We welcome people from all backgrounds, ethnicities, cultures, and experiences. Etsy is an equal opportunity employer. We do not discriminate on the basis of race, color, ancestry, religion, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender identity or expression, veteran status, or any other legally protected status. We will ensure that individuals with disabilities are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skillsets.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

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Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


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Data Scientist

Local Jobs TE Connectivity in Data Scientist
  • United States, Hampton, VA 23666 View on Map
  • Post Date: June 18, 2020
  • Apply Before : July 18, 2020
  • Share:

Job Description

  • The Manufacturing Data Analytics team is part of the Corporate Technology group focused to develop next generation solutions to support continuous improvement in the factory by leveraging IIoT and Systems data. We report to the Operations Lead for TE Connectivity.
  • This position will report to the Senior Manager, Manufacturing Data Analytics and is expected to support a variety of complex analysis and visualizations using big data technologies for globally dispersed manufacturing plants and processes
What your background should look like:
  • Daily work will involve one or more of the following activities
  • Build intimate relationships with factory improvement teams and manufacturing subject matter experts to increase process domain knowledge and ensure successful project outcomes.
  • Translate complex strategic challenge into relevant analytical framework.
  • Assume a leadership role to lead meetings, establish project plans, and report progress at regular intervals
  • Identify relevant structured and unstructured data sources available to support the improvement initiatives including IIoT, MES, Quality, and Maintenance systems.
  • Leverage Cloud services to perform efficient, comprehensive, and accurate data analysis on complex data sets.
  • Create statistical and machine learning models, delivering insight through visualization to support project improvement deliverables. Analytical approach will include but is not limited to six sigma, statistical analysis, regression, decision trees, neural networks, cluster analysis, mixed models, machine learning, deep learning, etc.
  • Build and deploy ML inference once models have been validated.
  • Build and maintain monitoring and alerting systems to ensure solution reliability and accuracy.
  • A rigorous understanding of the fundamentals of statistics, machine learning and artificial intelligence applied to business challenges and microeconomics is required.
  • Proficiency in development to such as R, Python, Java, and/or Spark is required.
  • Exposure to distributed computing frameworks as well as cloud technologies is required.
  • A strong curiosity to learn and apply data science techniques and tools is required.
  • Proven ability to work within a climate of ambiguity is necessary.
  • Outstanding communication and presentation skills is a must.
  • A graduate degree (MS or PhD) in STEM disciplines (Science, Technology, Engineering, Math) or in other disciplines with heavy focus on quantitative domains, including statistics, analytics, data science, computing or actuarial sciences is desired
Competencies
Values: Integrity, Accountability,Teamwork, Innovation


About TE Connectivity

TE Connectivity is a $13 billion global industrial technology leader creating a safer, sustainable, productive, and connected future. Our broad range of connectivity and sensor solutions, proven in the harshest environments, enable advancements in transportation, industrial applications, medical technology, energy, data communications, and the home. With nearly 80,000 employees, including more than 8,000 engineers, working alongside customers in approximately 150 countries, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn, Facebook, WeChat and Twitter.

What TE Connectivity offers:
We offer competitive total rewards compensation. Our commitment to our associates includes offering benefit programs that are comprehensive, competitive and will meet the needs of our associates.

  • Generous 401(k) Plan
  • Tuition Reimbursement
  • Benefits start on day one
  • Charity Donation Matching Program
  • Competitive Paid Time Off
  • Employee Resource Groups
  • Employee Stock Purchase Program
  • Healthcare for Associates and Families
  • Health and Wellness Incentives
  • Life Insurance and Disability Protection

Throughout our Global reach and various Business Units, we take a balanced approach to the benefits we provide. Many benefits are company-paid, while others are available through associate contribution. Specific benefit offerings can vary by location.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


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Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


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Data Scientist

Local Jobs Apple in Data Scientist
  • United States, Santa Clara Valley, CA 95014 View on Map
  • Post Date: June 13, 2020
  • Apply Before : July 13, 2020
  • Share:

Job Description

Summary

Posted: Jun 11, 2020
Weekly Hours: 40
Role Number:200175199
We are the Computer Vision Testing Group responsible for quality of many exciting projects (ARkit, Animoji, FaceID, etc.), that have been shipped on Apple products. We are now seeking a Camera Image Quality Engineer to stress test and provide responsible image quality feedback to developers. You will do hands-on image quality testing work, collaborate with developers, continuously track camera algorithm bugs and be able to represent image quality from a user’s perspective.
Key Qualifications
  • A curious mind
  • An obsession for quality
  • Background in Data science, Data mining, Multivariate statistics, Computer vision, Machine learning
  • Experience working with large scale data sets
  • Solid programming skills including:
  • Python
  • C/C++
  • Experience with data visualization and presentation, familiar with data analysis tools such as Tableau
  • Excellent problem solving and communication skills
Description
The Data Scientist will work closely with other members of the Video Engineering group to mine data, implement model evaluation pipeline, analyze large scale data, visualize data, and ensure the delivery is of the highest quality. This position will also require strong coding skills, presentation skills, and collaborating with multiple teams (ex: machine learning, cloud infrastructure support).
The responsibilities of this position includes but not limited to the following for current and future products:
– Implement algorithm evaluation methods
– Analyze data and build data analysis tools
– Deep-dive failure analysis
– Discover new perspectives for old data
– Produce / Present meaningful data visualization to higher-ups and across various involved teams
Education & Experience
PhD or Masters in Computer Science

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

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Data Scientist

Local Jobs Walmart in Data Scientist
  • United States, Carlsbad, CA 92008 View on Map
  • Post Date: June 12, 2020
  • Apply Before : July 12, 2020
  • Share:

Job Description

Position Description

We are seeking a Data Scientist professional in our Carlsbad, CA office.

Duties: Work with business stakeholders to understand the business requirements and the data available to solve corresponding problems. Translate business requirements into problems that can be solved using statistical and/or machine learning techniques. Build data sets from different sources for data analysis and model development, which will include wrangling, cleaning, and pre-processing data. Conduct exploratory data analysis to understand the patterns and potential business insights exhibited in the data. Create data visualizations to summarize the insights discovered during the data analysis and communicate them to internal team members and business stakeholders. Develop statistical and machine learning models to solve business problems and derive actionable business insights. Help deploy models in various formats. Derive metrics for model performance monitoring and conduct continuous model performance monitoring after deployment. Present insights discovered from data analysis and statistical and machine learning modeling and make recommendations based on the results to internal team members and business stakeholders.

#LI-DNP; #LI-DNI


Minimum Qualifications

Minimum education and experience required: Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Information Systems, Quantitative Methods, or related field and 1 year of analytics or data science experience; OR Bachelor’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Information Systems, Quantitative Methods, or related field and 2 years of analytics or data science experience.

Skills required: Experience data wrangling large data sets using Python and Spark on the GCP and Azure Cloud Computing Platforms. Experience conducting statistical data analysis and hypothesis testing using Python and R. Experience developing statistical models and machine learning models using Python and R. Experience creating data visualization and dashboards using Python Plotly and D3.js. Experience developing feature representations and deep learning models using TensorFlow and PyTorch. Experience extracting and querying data from databases using SQL. Employer will accept any amount of experience with the required skills.

Wal-Mart is an Equal Opportunity Employer.


Additional Preferred Qualifications

#LI-DNP; #LI-DNI


Company Summary

The Walmart eCommerce team is rapidly innovating to evolve and define the future state of shopping. As the world’s largest retailer, we are on a mission to help people save money and live better. With the help of some of the brightest minds in technology, merchandising, marketing, supply chain, talent and more, we are reimagining the intersection of digital and physical shopping to help achieve that mission.


Position Summary

We are seeking a Data Scientist professional in our Carlsbad, CA office.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

Other jobs you may like

Data Scientist

Local Jobs Cognizant Technology Solutions in Data Scientist
  • United States, St. Louis, MO 63101 View on Map
  • Post Date: June 11, 2020
  • Apply Before : July 11, 2020
  • Share:

Job Description

Job

summary

We

are looking for Data

Scientist building high-performing, scalable,

enterprise-grade applications. You will be part of a talented software team

that works on mission-critical applications.

Required

Qualifications :
These

are basic qualifications that the candidate must have in order to be considered

for the posted position. This includes but is not limited to:

  • Degree-specific

requirements – High School, Bachelors or Masters Degree, etc.

  • Total

of 2+ years of experience is required

  • Candidates

should be open to work out of St Louis, MO

  • Cognizant

will only consider applicants for this position whom are legally authorized

to work in the United States without company sponsorship (H-1B, L-1B,

L-1A, etc.).”

Roles and

Responsibilities:
·

Experience

of Linux shell script

·

Experience

working with and performing analysis using large data sets

o 10-1000 TB

·

Familiarity

with common data science toolkits, such as R, Jupyter, & Python

·

Knowledge

of traditional databases such as: Netezza, MySQL, Teradata, Oracle,

etc

·

Preferred

– Experience with Azure products: Azure Data Lake Store, Azure HD

Insights, Cosmos DB, PowerBI

Preferred

Skills:
Strong

commitment to quality

Understanding

of the full application life-cycle from inception through maintenance

Solves

new and/or familiar problems independently and without introducing regressions

Strong

oral and written communication skills

Ability

to work in a collaborative team environment

Employee Status : Full Time Employee

Shift : Day Job

Travel : No

Job Posting : Jun 10 2020

About Cognizant Cognizant (Nasdaq-100: CTSH) is one of the world’s leading professional services companies, transforming clients’ business, operating and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant is ranked 193 on the Fortune 500 and is consistently listed among the most admired companies in the world. Learn how Cognizant helps clients lead with digital at www.cognizant.com or follow us @USJobsCognizant.

Cognizant is recognized as a Military Friendly Employer and is a coalition member of the Veteran Jobs Mission. Our Cognizant Veterans Network assists Veterans in building and growing a career at Cognizant that allows them to leverage the leadership, loyalty, integrity, and commitment to excellence instilled in them through participation in military service.

Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender, identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

If you have a disability that requires a reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

Other jobs you may like

Data Scientist

Local Jobs Booz Allen Hamilton in Data Scientist
  • United States, Norfolk, VA 23502 View on Map
  • Post Date: June 11, 2020
  • Apply Before : July 11, 2020
  • Share:

Job Description

The Challenge:

Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities. As a data scientist, you can turn these complex data sets into useful information to solve global challenges. Across private and public sectors — from fraud detection, to cancer research, to national intelligence — you know the answers are in the data.

We have an opportunity for you to use your leadership and analytical skills to improve a client’s data science capability. You’ll work closely with your client to understand their questions and needs, and then dig into their data-rich environment to find the pieces of their information puzzle. You’ll mentor teammates, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help leadership make informed decisions. You’ll provide your customer with a deep understanding of their data, what it all means, and how they can use it. Join us as we use data science for good in building this capability.

Empower change with us.


You Have:

  • 4 years of experience in the data science field, including providing analysis and advice
  • Experience with building and optimizing Big Data pipelines, architectures, and data sets
  • Experience with visualizing data and producing high quality graphs and charts
  • Experience with the preparation and development of senior leadership level background papers, reports, and speeches
  • Ability to use office tools, including Microsoft Office
  • Secret clearance
  • BA or BS degree

Nice If You Have:
  • Experience with multiple programming languages, including Python, C++, R, MATLAB, or SAS
  • Experience with Big Data architecture platforms and extracting information from disparate data sources, then merging them together for analysis
  • Knowledge of various machine learning algorithms, statistics, and mathematics principles
  • Knowledge of advanced machine learning capabilities, including gradient boosting, random forests, or convolutional neural networks
  • Ability to learn new programming languages


Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.


Build Your Career:

At Booz Allen, we know the power of analytics and we’re dedicated to helping you grow as a data analysis professional. When you join Booz Allen, you’ll have the chance to:

  • access online and onsite training in data analysis and presentation methodologies, and tools like Hortonworks, Docker, Tableau, and Splunk
  • change the world with the Data Science Bowl—the world’s premier data science for social good competition
  • participate in partnerships with data science leaders, like our partnership with NVIDIA to deliver Deep Learning Institute (DLI) training to the federal government

You’ll have access to a wealth of training resources through our Analytics University, an online learning portal specifically geared towards data science and analytics skills, where you can access more than 5000 functional and technical courses, certifications, and books. Build your technical skills through hands-on training on the latest tools and state-of-the-art tech from our in-house experts. Pursuing certifications that directly impact your role? You may be able to take advantage of our tuition assistance, on-site bootcamps, certification training, academic programs, vendor relationships, and a network of professionals who can give you helpful tips. We’ll help you develop the career you want as you chart your own course for success.

We’re an EOE that empowers our people—no matter their race, color, religion, sex, gender identity, sexual orientation, national origin, disability, veteran status, or other protected characteristic—to fearlessly drive change.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

Other jobs you may like

Data Scientist

Local Jobs PayPal in Data Scientist
  • United States, Timonium, MD 21093 View on Map
  • Post Date: June 10, 2020
  • Apply Before : July 10, 2020
  • Share:

Job Description

Responsibilities:

  • Develop loss forecasts for global credit products leveraging internal performance data and various macroeconomic inputs
  • Conduct regular stress testing to ensure portfolio maintains minimum profitability measures
  • Participate in monthly/quarterly reserve setting process with Finance and Accounting
  • Monitor global portfolio performance to ensure its within PayPal’s Credit Risk Appetite
  • Partner with Operations to conceive, design & monitor strategies to improve credit losses
  • Leverage internal and external data to enhance existing models and business rules
  • Analyze portfolio trends to deliver strategic loss forecasting insights
  • Communicate concise and actionable business strategies to Executive team


Qualifications:

  • Bachelor’s degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline.
  • 5+ years of proven Risk and Collections experience in Financial Services, Payment Transactions or other financial related industry
  • Analytical and project management experience
  • Excel and spreadsheet analysis
  • Handling and building complex formulas in Excel spreadsheet
  • Risk Management
  • Collections strategy
  • Statistical analysis
  • Loss modeling
  • Building complex forecasting model using advanced Excel functions
  • SAS (R or Python) and SQL skills to be able to run data queries and research risk strategy and collections impacts
  • Using PowerPoint for management communications and broad organizational readouts
  • Any suitable combination of education, training and experience is acceptable.

Job_Description_Summary: PayPal’s Credit Risk Organization is responsible for managing risk throughout the customer lifecycle. This is an exciting organization where contributions have a direct P&L impact. The Data Scientist will collaborate with Strategy, Operations, Finance, and Technology to predict and understand PayPal’s credit losses.

Who we are: Fueled by a fundamental belief that having access to financial services creates opportunity, PayPal (NASDAQ: PYPL) is committed to democratizing financial services and empowering people and businesses to join and thrive in the global economy. Our open digital payments platform gives PayPal’s 286 million active account holders the confidence to connect and transact in new and powerful ways, whether they are online, on a mobile device, in an app, or in person. Through a combination of technological innovation and strategic partnerships, PayPal creates better ways to manage and move money, and offers choice and flexibility when sending payments, paying or getting paid. Available in more than 200 markets around the world, the PayPal platform, including Braintree, Venmo and Xoom enables consumers and merchants to receive money in more than 100 currencies, withdraw funds in 56 currencies and hold balances in their PayPal accounts in 25 currencies.

We’re a purpose-driven company whose beliefs are the foundation for how we conduct business every day. We hold ourselves to our One Team Behaviors which demand that we hold the highest ethical standards, to empower an open and diverse workplace, and strive to treat everyone who is touched by our business with dignity and respect. Our employees challenge the status quo, ask questions, and find solutions. We want to break down barriers to financial empowerment. Join us as we change the way the world defines financial freedom.

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities.

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

Other jobs you may like

Data Scientist

Local Jobs Comcast in Data Scientist
  • United States, Philadelphia, PA View on Map
  • Post Date: June 9, 2020
  • Apply Before : July 9, 2020
  • Share:

Job Description

Business Unit:

The Device Software Product Management team is responsible for the management of software strategy & roadmap for all Comcast & Sky devices. This generally includes a broad set of responsibilities including: strategy development, product discovery of new technologies, external & internal partnerships, software roadmap definition, management and prioritization for new and existing devices.


As a data scientist, you will play a pivotal role in improving Comcast’s WiFi product! You will collaborate with a multi-disciplinary team of engineers, architects, product managers and external partners to derive key insights that will be used for decision making, producing reports for both internal consumption and TPX SLT and driving device/platform requirements and improvements!


Core Responsibilities:


  • Work with large, complex data sets and apply analytical and statistical methods to derive global and local trends relative to WiFi performance for both CPE & connected clients and associated operational metrics.

  • Synthesize trends into insights to make product recommendations with effective presentations of findings at multiple levels of partners through visual display of quantitative information

  • Build and prototype analysis pipeline iteratively to provide insights at scale. Develop understanding of Comcast data structures and metrics, advocating for changes where needed for both product and platform development.

  • Establish performance baselines, develop and deploy predictive models to forecast improvements, keep track of benefits realization as new features are developed & deployed

  • May serve as team leader. Mentors and trains junior team members.


Qualifications:

  • MS degree in a quantitative discipline (e.g., data analytics, statistics, operations research, bioinformatics, computer science, mathematics, physics, electrical engineering, industrial engineering).

  • 3-5 years of meaningful work experience in data analysis or related field. (e.g., as an engineer, data scientist)

  • Strong sense of independence and intellectual curiosity.

  • Ability to think, communicate and execute from big picture strategy to execution details

  • Strong foundation in data analytics, statistics and machine learning

  • Experience in writing code in SQL & Python (Scala, Unix)

  • Experience in operating in Big Data Pipelines (Spark, Hive, SQL engines) batch and streaming

  • Experience in developing and deploying Machine Learning models and data story telling with visualizations


Preferred qualifications:


  • PhD degree in a quantitative discipline as listed in Minimum Qualifications

  • Applied experience with machine learning on large datasets (Spark)

  • Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations.

  • Demonstrated skills in selecting the right statistical tools given a data analysis problem. Proven effective written and verbal communication skills.

  • Displayed leadership and self-direction. Showcased willingness to both teach others and learn new techniques.


Comcast is an EOE/Veterans/Disabled/LGBT employer

Data Science Courses

Data Scientist Masters Program

Data Scientist Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

VIEW COURSE


Data Science for Everyone

Data Science for Everyone

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

VIEW COURSE


Data Science for Business

Data Science for Business

What is data science and how can you use it to strengthen your organization? This course will teach you about the skills you need on your data team, and how you can structure that team to meet your organization’s needs. Data is everywhere! This course will provide you with an understanding of data sources your company can use and how to store that data. You’ll also discover ways to analyze and visualize your data through dashboards and A/B tests. To wrap up the course, we’ll discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI! Along the way, you’ll learn about a variety of real-world applications of data science and gain a better understanding of these concepts through practical exercises.

VIEW COURSE


Read More

Data Science Books

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

Cloud Computing Architecture: Technologies and Practice (Advances in Computer Science)

The book begins by establishing the concept of cloud computing and describing the technological trends, and then discusses cloud computing architecture connotation and key technologies such as computing, storage, network, data, management, access, and security. With abundant project experiences and applications, the book is an essential reference for researchers and industrial engineers in computer science and information management.ed manner

VIEW BOOK


Big Data on Campus: Data Analytics and Decision Making in Higher Education

Big Data on Campus: Data Analytics and Decision Making in Higher Education

The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities.

VIEW BOOK


Big Data with Hadoop MapReduce: A Classroom Approach

Big Data with Hadoop MapReduce: A Classroom Approach

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines.

VIEW BOOK


Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Customer Data and Privacy: The Insights You Need from Harvard Business Review (HBR Insights Series)

Is it possible to take advantage of the benefits of data collection–and mitigate risks–for both companies and customers?

Most consumers are not very skilled at evaluating privacy risks; they’re either unable to determine the cost of sharing personal data online or unaware of what they’re sharing. (Doesn’t everyone scroll down without reading to click “I accept”?) Without much intervention from most federal or state-level governments, companies are on their own to define what qualifies as reasonable use. In today’s digital surveillance economy, there are no clear-cut best practices or guidelines. Gathering and using information can help customers–we see that in personalization and autofill of online forms. But companies must act in the best interest of their customers and treat the sensitive information users give them with the ethical care of doctors, lawyers, and financial advisers. The challenges of operating in a digital ecosystem aren’t going away. Customer Data and Privacy: The Insights You Need from Harvard Business Review will help you understand the tangled interdependencies and complexities and develop strategies that allow your company to be good stewards, collecting, using, and storing customer data responsibly.

VIEW BOOK


Read More

Other jobs you may like