Salary for Senior-level / Expert Data Scientist in United States during 2024

Salary details

The average senior-level / expert Data Scientist salary lies between USD 130,000 and USD 210,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Jan. 19, 2025

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Scientist roles

The three most common job tag items assiciated with senior-level / expert Data Scientist job listings are Python, Machine Learning and Statistics. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Python | 7383 jobs Machine Learning | 6879 jobs Statistics | 6485 jobs Engineering | 5595 jobs SQL | 5448 jobs Computer Science | 4269 jobs Mathematics | 3903 jobs R | 3757 jobs Research | 3682 jobs ML models | 3009 jobs Data analysis | 2537 jobs Testing | 2419 jobs AWS | 2411 jobs Deep Learning | 2176 jobs PhD | 1977 jobs Pipelines | 1962 jobs Spark | 1923 jobs NLP | 1833 jobs TensorFlow | 1724 jobs Data visualization | 1680 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Scientist roles

The three most common job benefits and perks assiciated with senior-level / expert Data Scientist job listings are Career development, Health care and Equity / stock options. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 6634 jobs Health care | 3406 jobs Equity / stock options | 2658 jobs Startup environment | 2233 jobs Flex hours | 2145 jobs Salary bonus | 1998 jobs Competitive pay | 1959 jobs Insurance | 1699 jobs Parental leave | 1483 jobs Team events | 1467 jobs Medical leave | 1415 jobs Flex vacation | 1392 jobs Wellness | 899 jobs 401(k) matching | 793 jobs Conferences | 464 jobs Fitness / gym | 337 jobs Unlimited paid time off | 336 jobs Home office stipend | 333 jobs Flexible spending account | 309 jobs Transparency | 268 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Scientist typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies and startups, potentially adding another 5% to 15% to the total compensation. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets.

Increasing Salary Further

To increase your salary beyond the median level, consider pursuing leadership roles such as Lead Data Scientist or Data Science Manager. These positions often come with higher compensation due to increased responsibilities. Additionally, specializing in high-demand areas like machine learning engineering, AI ethics, or big data analytics can make you more valuable. Networking within industry-specific conferences and contributing to open-source projects can also enhance your visibility and reputation, potentially leading to higher-paying opportunities. Negotiating your salary based on market research and leveraging offers from other companies can also be effective strategies.

Educational Requirements

Most Senior-level Data Scientist positions require at least a Master's degree in a relevant field such as Computer Science, Statistics, Mathematics, or Data Science. A Ph.D. is often preferred, especially for roles that involve complex research and development tasks. The educational background should provide a strong foundation in statistical analysis, machine learning, and programming. Additionally, coursework or experience in business analytics can be beneficial, as it helps in understanding the business implications of data-driven decisions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty are well-regarded in the industry. These certifications validate your skills in specific tools and methodologies, making you a more attractive candidate for senior roles. Additionally, completing online courses from platforms like Coursera or edX in advanced machine learning or data science topics can also be advantageous.

Required Experience

Typically, a Senior-level Data Scientist is expected to have at least 5 to 10 years of experience in data science or related fields. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in leading projects, mentoring junior data scientists, and collaborating with cross-functional teams is also crucial. Demonstrated success in solving complex business problems using data-driven approaches is often a key requirement.

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