Over the past decade, our global focus has shifted more and more towards data and the field of data science has seen tremendous growth. The demand and salary attached to the coveted data scientist career remains high. The Bureau of Labor Statistics (BLS) claims that jobs for computer and information research scientists, which includes data scientists will experience 14% growth through 2028 and a data scientist’s average salary is $118,370 per year. However, a data scientist’s starting salary may be lower than the average.
Salaries for data scientists depend on their experience, where they work, and what industry they work in. According to IBM’s study from 2017, The Quant Crunch – How the Demand for Data Science Skills is Disrupting the Job Market, data centered skills saw significant growth and the demand for data science as a skill increased by 40%.
Additionally, IBM claims that companies are searching for individuals who understand machine learning, artificial intelligence, and big data and that professionals with more work experience on their resumes are in higher demand than their entry level counterparts. Finally, folks living on the east or west coast enjoy base salaries close to $130,000 on average, almost $15,000 more than the median salary according to the BLS.
This data scientist salary guide will help you understand how experience, location, and industry impact a data scientist’s salary and some recommendations to maximize your earning potential.
Top Paying Locations/States for Data Scientists
Salaries for data scientists vary by region and state. According to the BLS, the bottom 10 percent earned less than $69,230, and the highest 10 percent earned over $183,8200 on average per year. Depending on the employer, some data scientists may even work remotely, getting the best of both worlds: living where they want and maximizing their earning potential through working for a company that pays a salary higher than the average.
Overall, data scientists working in California, New York, and Washington enjoy some of the highest salaries among all of the states the BLS has data on. These regions are considered major tech hubs, the homes of Silicon Valley (California) and Silicon Alley (New York), as well as tech giants, including Amazon, one of the largest players in the Seattle tech scene in Washington state. But you don’t have to live on the coast or a major city to earn a high salary working in data science. In fact, New Mexico and Virginia boast average salaries of over $125,000 per year. However, states with major cities, such as Massachusetts and Illinois do pay their data scientists above the median salary.
It’s important to note that the BLS did not have median wage data for 18 states, including Alabama, Alaska, Connecticut, Delaware, Idaho, Indiana, Iowa, Kentucky, Louisiana, Maine, New Hampshire, North Dakota, Oregon, South Carolina, South Dakota, Vermont, West Virginia, and Wyoming. Here’s a breakdown of the five top paying states for computer and information research scientists, including data scientists, in the BLS database:
- Washington: $143,080
- California: $136,310
- Virginia: $129,840
- Texas: $125,800
- Maryland: $119,180
Data Scientist Salary by Working Experience
Salary is dependent on work experience and in the field of data science, the more experience you have, the higher your paycheck. Here, we lay out what you can expect to earn as you move through the ranks from entry level to junior level and senior, to managerial positions. It’s important to note that these averages might be more or less depending on where you live and the industry you work in.
According to a report from Burtchworks on the salaries of Data Scientists in 2018, entry level data scientists with zero to three years of experience can expect to earn on average, $94,987 per year. An employee who has between four to eight years of experience may be considered a junior data scientist and can earn on average, $128,750 per year. A senior data scientist, with over eight years of experience can earn on average, $165,000 per year.
At the managerial level, a data scientist manager’s salary climbs even higher and there’s a positive correlation between the size of the team that a manager supervises and their salary. A manager with a small team may earn an average salary of $146,133 per year, a manager with a medium sized team earns on average $185,000 per year, and a manager with a large team earns an average salary of $250,000 per year.
Data Scientist Salary by Industry
Data scientists can be useful in almost any industry. According to the Burtchworks study, the largest employers of data scientists are in the tech industry, which includes cloud services, hosting, and social networks. The tech industry employs about 44% of all talent. 14% of working data scientists are employed by banking and finance companies, making financial services the second largest sector hiring for data scientists.
According to the study, on average, data scientists working in the tech industry earn higher base salaries than those employed in other industries, which may make it a great place for burgeoning data scientists to look to during their job search. Entry level salaries in tech start at around $94,345. Managers can earn an average salary of $152,194 and senior managers can make $254,636 a year. The average salary for other sectors, including banking and finance are a bit lower at managerial levels, but entry level jobs in other sectors typically start at around $95,261.
It’s important to note that differences in salary may have to do with the skills professionals in these industries can perform. It’s possible to earn a higher average salary in most industries with the right skillset. In fact, possessing in demand skills may give candidates an edge over their competition. According to IBM’s study, high-paying skills in finance include MATLAB, mergers and acquisitions, data warehousing, project management, and R.
Higher paying skills for data scientists in other sectors include pattern recognition, database schemas, quantitative analysis, and database administration, and many of these skills are related to big data. Individuals with these skills on their resumes can potentially earn higher salaries on average than those who have skills that are in less demand.