Skip to Content
2016 Data Science Salary Survey
book

2016 Data Science Salary Survey

by John King, Roger Magoulas
September 2016
Beginner
40 pages
46m
English
O'Reilly Media, Inc.
Content preview from 2016 Data Science Salary Survey

How You Spend Your Time

Importance of Tasks

The type of work respondents do was captured through four different types of questions:

  • involvement in specific tasks
  • job title
  • time spent in meetings
  • time spent coding

For every task, respondents chose from three options: no engagement, minor engagement, or major engagement.

The task with the greatest impact on salary (i.e., the greatest coefficient) was developing prototype models. Respondents who indicated major engagement with this task received on average a $7.4K boost, based on our model. Even minor engagement in developing prototype models had a +4.4 coefficient.

Relevance of Job Titles

When both tasks and job titles are included in the training set, job title “wins” as a better predictor of salary. It’s notable however, that titles themselves are not necessarily accurate at describing what people do. For example, even among architects there was only a 70% rate of major engagement in planning large software projects—a task that theoretically defines the role. Since job title does perform well as a salary predictor, despite this inconsistency, it may be that “architect,” for example, is a symbol of seniority as much as anything else.

Respondents with “upper management” titles—mostly C-level executives at smaller companies, directors and VPs—had a huge coefficient of +20.2. Engagement in tasks associated with managerial roles also had a positive impact on salary, namely: organizing team projects (+9.7), identifying business ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

AirBnbBlueOriginElectronic ArtsHomeDepotNasdaqRakutenTata Consultancy Services

QuotationMarkO’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
Julian F.
Head of Cybersecurity
QuotationMarkI wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.
Addison B.
Field Engineer
QuotationMarkI’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.
Amir M.
Data Platform Tech Lead
QuotationMarkI'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Mark W.
Embedded Software Engineer

You might also like

2017 Data Science Salary Survey

2017 Data Science Salary Survey

Brian Suda
2015 Data Science Salary Survey

2015 Data Science Salary Survey

John King, Roger Magoulas

Publisher Resources

ISBN: 9781492049029Errata Page