2016 Data Science Salary Survey

2016 Data Science Salary Survey

Author: John King

Publisher:

Published: 2016

Total Pages:

ISBN-13: 9781492049029

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In this fourth edition of O'Reilly's Data Science Salary Survey, 983 respondents working across a variety of industries answered questions about the tools they use, the tasks they engage in, and the salaries they make. This year's survey includes data scientists, engineers, and others in the data space from 45 countries and 45 US states. The 2016 survey included new questions, most notably about specific data-related tasks that may affect salary. Plug in your own data points to the survey model and see how you compare to other data science professionals in your industry. With this report, you'll learn: Where data scientists make the highest salaries-by country and by US state Tools that respondents most commonly use on the job, and tools that contribute most to salary Two activities that contribute to higher earnings among respondents How gender and bargaining skills affect salaries when all other factors are equal Salary differences between those using open source tools vs those using proprietary tools Salary differences between those who rely on Python vs those who use several tools Participate in the 2017 Survey The survey is now open for the 2017 report. Spend just 5 to 10 minutes and take the anonymous salary survey here: https://www.oreilly.com/ideas/take-the-2​017-data-science-salary-survey .


2017 Data Science Salary Survey

2017 Data Science Salary Survey

Author: Brian Suda

Publisher:

Published: 2018

Total Pages:

ISBN-13: 9781491997079

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Get a clear picture of the salaries and bonuses data science professionals around the world receive, as well as the tools and cloud providers they use, the tasks they perform, and how interpersonal ("soft") skills might affect their pay. The fifth edition of O'Reilly's online Data Science Salary Survey provides complete results from nearly 800 participants from 69 different countries, 42 different US states, and Washington, DC. With five years of data, the survey's results are consistent enough to reliably identify changes and trends. The survey asked specific questions about industry, team, and company size, but also posed questions such as, "How easy is it to move to another position?" or "What is your next career step?" You can plug in your own data points to the survey model and see how you compare to other data science professionals in your industry. With this report, you'll learn: Where data scientists make the highest salaries-by country and by US state Tools that respondents most commonly use on the job, and tools that contribute most to salary Activities that contribute to higher earnings How gender and bargaining skills affect salaries when all other factors are equal Salary differences between those using open source tools vs those using proprietary tools How the increase in respondents outside of the US signal a rise in international companies starting and growing data organizations Participate in the 2018 Survey: Spend just 5 to 10 minutes and take the anonymous salary survey here: https://www.oreilly.com/ideas/take-the-​data-science-salary-survey .


The 2015 O'Reilly Data Science Salary Survey

The 2015 O'Reilly Data Science Salary Survey

Author: Roger Magoulas

Publisher:

Published: 2016

Total Pages:

ISBN-13:

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"The 2015 O'Reilly Data Science Salary Survey provides insights that could significantly impact your career in data science. The video starts with a longitudinal look at what's common across the surveys O'Reilly's done over the last three years, then moves through the latest results and the process for gathering and analyzing the data. The Survey's research derives from data collected in 2015 through online surveys. It includes demographic information, time spent on various data-related tasks, and the use or non-use of 116 software tools. Data came from over 600 respondents working in a variety of industries, two-thirds of whom are based in the United States."--Resource description page.


2013 Data Science Salary Survey

2013 Data Science Salary Survey

Author: John King

Publisher:

Published: 2014

Total Pages:

ISBN-13: 9781492044475

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What tools do successful data scientists and analysts use, and how much money do they make? We surveyed hundreds of attendees at the O'Reilly Strata Conferences in Santa Clara, California and New York to understand. Findings from the survey include: Average number of tools and median income for all respondents Distribution of responses by age, location, industry, and position Detailed analysis of tools used by respondents and correlation to their salaries - including by tool clusters (Hadoop, SQL/Excel, and other) Correlation of specialized big data tools usage and salary What tools should you be learning and using? Read this valuable report to gain insight from these potentially career-changing findings.


Data Science Thinking

Data Science Thinking

Author: Longbing Cao

Publisher: Springer

Published: 2018-08-17

Total Pages: 404

ISBN-13: 3319950924

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This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.