Salary for Senior-level / Expert Data Scientist during 2023

Salary details

The average senior-level / expert Data Scientist salary lies between USD 134,236 and USD 205,000 globally. 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.

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 2023 and the number of open jobs that where associated with them during that period:

Python | 2586 jobs Machine Learning | 2319 jobs Statistics | 2213 jobs SQL | 2077 jobs Engineering | 1924 jobs Computer Science | 1387 jobs R | 1287 jobs Mathematics | 1284 jobs Research | 1226 jobs ML models | 947 jobs Testing | 761 jobs Spark | 696 jobs Data analysis | 680 jobs Tableau | 658 jobs AWS | 646 jobs Deep Learning | 604 jobs PhD | 588 jobs Big Data | 567 jobs Pipelines | 564 jobs Economics | 559 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 2023 and the number of open jobs that where offering them during that period:

Career development | 2154 jobs Health care | 1045 jobs Equity / stock options | 815 jobs Startup environment | 798 jobs Flex hours | 776 jobs Competitive pay | 694 jobs Team events | 671 jobs Flex vacation | 653 jobs Salary bonus | 563 jobs Parental leave | 552 jobs Insurance | 533 jobs Medical leave | 381 jobs Wellness | 369 jobs 401(k) matching | 329 jobs Home office stipend | 260 jobs Unlimited paid time off | 229 jobs Conferences | 144 jobs Fitness / gym | 119 jobs Relocation support | 96 jobs Gear | 91 jobs

Salary Composition for Senior-Level Data Scientists

The salary for a Senior-level or Expert Data Scientist typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The composition can vary significantly based on region, industry, and company size. In the United States, for instance, tech hubs like Silicon Valley or New York City often offer higher base salaries and substantial equity packages compared to other regions. In contrast, companies in the finance or healthcare sectors might offer higher bonuses tied to performance metrics. Smaller startups might offer lower base salaries but compensate with significant equity stakes, while larger corporations might provide more stable base salaries with moderate bonuses and stock options.

Steps to Increase Salary from a Senior-Level Position

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

• Specialization: Develop expertise in niche areas such as deep learning, natural language processing, or AI ethics, which are in high demand.
• Leadership Roles: Transition into leadership roles such as Data Science Manager or Director of Data Science, where strategic decision-making and team management skills are crucial.
• Consulting: Explore opportunities in consulting, where you can leverage your expertise across multiple projects and industries, often commanding higher fees.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, which can make you indispensable to your organization.

Educational Requirements

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

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some valuable certifications include:

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

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Experience Requirements

Typically, a Senior-level Data Scientist is expected to have at least 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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