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Book Description

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.

Table of Contents

  1. Take the Data Science Salary Survey
  2. 2017 Data Science Salary Survey
  3. 1. Executive Summary
  4. 2. Introduction
  5. 3. Salary
    1. By World Region
    2. By State
    3. By Gender
    4. By Age
    5. By Experience
    6. Industry
    7. Education
    8. Company Age
    9. Company Size
    10. Job Titles
    11. Time Spent in Meetings
    12. Time Spent Coding
    13. Length of Work Week
    14. Ease of Finding a New Role
    15. Self-Assessed Bargaining Skills
    16. Advance Your Career
  6. 4. Work Setup and Tools
    1. Operating Systems
    2. Programming Languages
    3. Relational Databases
    4. Hadoop
    5. Search
    6. Big Data Platforms
    7. Business Intelligence and Reporting
    8. Machine Learning
    9. Viz Tools
    10. Importance of Tasks
  7. 5. Conclusion
    1. Model
  8. 6. We need your data.
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