On average data scientists are earning almost six figure salaries, with top earners making $135,000 or more annually, according to data from Paysa, a platform evaluating compensation and the market rate for salaries. Paysa's analysis was based on information on 16,000 profiles, which includes base salary, equity and bonuses.
Cities with competitive tech markets pay more for data scientists, with San Francisco and Seattle paying $121,000 and $120,000, respectively, according to Paysa. Other cities with leading data scientist salaries, however, are emerging tech hubs such as Los Angeles, Boston and Austin, Texas.
In particular, technology companies pay the most for data scientists, though it is becoming more common for other sectors to bring in data scientists. Snap Inc., Airbnb, Pinterest, Lyft and etsy are the best-paying companies for data scientists, according to Paysa. Compensation for those companies at least $140,000 in base salary with total compensation between $183,000 and $238,000.
As companies become more digitally savvy, focus has turned from legacy roles to forward-looking hires who can tap into the world's newest currency: data.
Data scientists are among the most in-demand roles in the tech sphere, along with business intelligence analysts, developers and cybersecurity experts, according to the 2018 salary guide from Robert Half.
Highly valued in the enterprise, salaries for data specialists can fall in line with those in technology leadership positions.
There's a reason for the high price point: With increased, seemingly endless storage capacity, companies have freely amassed data troves. Organizations can collect everything from customer data to product usage patterns to technology performance.
Left with too much data to easily sift through and manage, employers turn to data scientists, tapping into analytical and technical skills.
As Boeing CIO Ted Colbert puts it, data's potential is "trapped" without proper guidance and management. To help increase engagement and allow for easier data interaction, scaling analytics and democratizing data capabilities is imperative, Colbert said.
Just having large data troves isn't enough. Without a data management program in place with the right experts, companies are missing an opportunity to drive profit and organizational change.