If you are wondering how much a data scientist earns, whether you are a hiring manager or looking for a job, there are plenty of websites providing rather detailed information, broken down by area, seniority, and skills. Here I focus on the United States, offering a summary based on various trusted websites.
A starting point is LinkedIn. Sometimes, the salary attached to a position is listed, and LinkedIn will tell you how many people viewed the job ad, and how well you fit based on skill matching and experience. LinkedIn will even tell you which of your connections work for the company in question, so you may contact the most relevant ones. Positions with fewer views, that are two week old, are less competitive (but maybe less attractive too), but if you don't have much experience, they could be worth applying to. You probably receive such job ads in your mailbox, from LinkedIn, every week. If not, you need to work on your LinkedIn profile (or maybe you don't want to receive such emails).
Popular websites with detailed information include PayScale, GlassDoor, and Indeed. GlassDoor, based on 17,000 reported salaries (see here), mentions a range from $82k to $165k, with an average of $116k per year for a level-2 data scientist. It climbs to $140k for level-3. You can do a search by city or company. Some companies listed include:
These are base salaries and do not include bonus, stock options, or other perks. Companies with many employees in the Bay Area offer bigger salaries due to the cost of living. These statistics may be somewhat biased as very senior employees are less likely to provide their salary information. A chief data scientist typically makes well above $200k a year, not including bonuses, and an $800k salary, at that level, at companies such as Microsoft or Deloitte (based on my experience), is not uncommon. On the low end, you have interns and part-time workers. If you visit Glassdoor, you can get much more granular data.
Below are statistics coming this time from Indeed (see here). They offer a different perspective, with breakdown by type of expertise and area. The top 5 cities with highest salaries are San Francisco ($157,041), Santa Clara ($156,284), New York ($140,262), Austin ($133,562) and San Diego ($124,679). Surprisingly, the pay is lower in Seattle than in Houston. Note that if you work remotely for a company in the Bay Area, you may get a lower salary if you live in an area with lower cost of living. Still, you would be financially better off than your peers in San Francisco.
The kind of experience commanding the highest salary (20 to 40% above average) are Cloud Architecture, DevOps, CI/CD (continuous delivery and/or continuous deployment), Microservices, and Performance Marketing. Finally, Indeed also displays salaries for related occupations, with the following averages:
The average for Data Scientist is $119,444 according to Indeed. This number is similar to the one coming from Glassdoor. Note that some well-funded startups can offer large salaries. My highest salary was as chief scientist / co-founder at a company with less than 20 employees. And my highest compensation was for a company I created and funded myself, though I was not on a payroll and I did not assign myself a job title.
To receive a weekly digest of our new articles, subscribe to our newsletter, here.
About the author: Vincent Granville is a data science pioneer, mathematician, book author (Wiley), patent owner, former post-doc at Cambridge University, former VC-funded executive, with 20+ years of corporate experience including CNET, NBC, Visa, Wells Fargo, Microsoft, eBay. Vincent is also self-publisher at DataShaping.com, and founded and co-founded a few start-ups, including one with a successful exit (Data Science Central acquired by Tech Target). He recently opened Paris Restaurant, in Anacortes. You can access Vincent's articles and books, here.