Salary for Senior-level / Expert Data Scientist in United States during 2022

Salary details

The average senior-level / expert Data Scientist salary lies between USD 136,000 and USD 190,000 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: Nov. 17, 2024

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 2022 and the number of open jobs that where associated with them during that period:

Python | 1738 jobs Machine Learning | 1476 jobs Statistics | 1327 jobs SQL | 1310 jobs Engineering | 1242 jobs Computer Science | 943 jobs R | 904 jobs Research | 904 jobs Mathematics | 754 jobs Testing | 643 jobs ML models | 610 jobs PhD | 478 jobs Spark | 456 jobs Pipelines | 443 jobs AWS | 437 jobs Economics | 416 jobs Data analysis | 390 jobs Deep Learning | 388 jobs Tableau | 371 jobs NLP | 346 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 Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 1393 jobs Health care | 643 jobs Startup environment | 570 jobs Flex vacation | 469 jobs Flex hours | 449 jobs Equity / stock options | 398 jobs Team events | 388 jobs Parental leave | 381 jobs Insurance | 321 jobs Competitive pay | 305 jobs Medical leave | 256 jobs Wellness | 253 jobs Salary bonus | 246 jobs 401(k) matching | 188 jobs Home office stipend | 165 jobs Conferences | 110 jobs Unlimited paid time off | 106 jobs Fitness / gym | 93 jobs Travel | 68 jobs Snacks / Drinks | 62 jobs

Salary Composition for Senior-Level Data Scientists

The salary for a Senior-level or Expert Data Scientist in the United States typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the most significant portion, often accounting for 70-80% of the total compensation package. Bonuses can vary widely, ranging from 10-20% of the base salary, depending on the company's performance and individual contributions. Additional remuneration, such as stock options, is more common in larger tech companies and startups, where it can form a substantial part of the total compensation, sometimes equaling or exceeding the base salary.

Regional differences also play a role. For instance, salaries in tech hubs like San Francisco, New York, and Seattle tend to be higher due to the cost of living and competition for talent. Industry-wise, tech companies, finance, and healthcare often offer higher salaries compared to academia or government roles. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Steps to Increase Salary from a Senior-Level Position

To increase your salary further from a Senior-level Data Scientist position, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand and can command higher salaries.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. Pursuing advanced certifications or courses can enhance your skill set and make you more valuable.
• Networking and Industry Engagement: Attend conferences, workshops, and networking events to connect with industry leaders and explore new opportunities.
• Negotiate Offers: When considering new job offers, negotiate for higher salaries or better compensation packages, leveraging your experience and expertise.

Educational Requirements for Senior-Level Data Scientists

Most Senior-level Data Scientist positions require at least a Master's degree in a relevant field such as Computer Science, Statistics, Mathematics, or Engineering. A Ph.D. is often preferred, especially for roles that involve research or developing new algorithms. The educational background should provide a strong foundation in statistical analysis, machine learning, and data manipulation.

Helpful Certifications for Data Scientists

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise in specific areas. Some valuable certifications include:

• Certified Data Scientist (CDS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Data Engineer

These certifications can validate your skills and knowledge, making you more competitive in the job market.

Experience Required for Senior-Level Data Scientists

Typically, a Senior-level Data Scientist is expected to have 5-10 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 highly valued.

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