Salary for Senior-level / Expert Data Scientist during 2024

Salary details

The average senior-level / expert Data Scientist salary lies between USD 124,600 and USD 209,000 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: 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

The salary for a Senior-level or Expert Data Scientist typically comprises several components, which can vary based on region, industry, and company size. Generally, the salary is divided into:

• Base Salary: This is the fixed annual amount and usually forms the largest portion of the total compensation. In the U.S., for example, this can range from 60% to 80% of the total package, depending on the company and location.

• Bonus: Performance-based bonuses are common and can range from 10% to 20% of the base salary. These bonuses are often tied to individual performance, team performance, or company profitability.

• Equity/Stock Options: Particularly in tech companies and startups, equity can be a significant part of the compensation package. This can vary widely but often constitutes 10% to 30% of the total compensation, especially in high-growth companies.

• Other Benefits: These can include health insurance, retirement contributions, and other perks like wellness programs, which can add significant value to the overall compensation package.

Increasing Salary Further

To increase your salary beyond the median of USD 165,000, 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: Transitioning into leadership or managerial roles, such as a Lead Data Scientist or Head of Data Science, can significantly increase your earning potential.

• Consulting or Freelancing: Offering your expertise as a consultant or freelancer can provide additional income streams and potentially higher hourly rates.

• Continuous Learning and Networking: Engage in continuous learning through advanced courses or certifications and expand your professional network to open up higher-paying opportunities.

Educational Requirements

For a Senior-level Data Scientist position, the most common educational requirements include:

• Advanced Degrees: A Master's degree in a relevant field such as Computer Science, Statistics, Mathematics, or Data Science is often required. A Ph.D. can be advantageous, especially for roles involving research or advanced algorithm development.

• Strong Foundation in Mathematics and Statistics: A solid understanding of statistical methods, linear algebra, and calculus is crucial.

• Programming Skills: Proficiency in programming languages such as Python, R, and SQL is essential.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate expertise:

• Certified Data Scientist (CDS): Offered by various institutions, this certification validates your skills in data science methodologies and tools.

• TensorFlow Developer Certificate: Demonstrates proficiency in building and deploying machine learning models using TensorFlow.

• AWS Certified Machine Learning – Specialty: Validates your ability to design, implement, and maintain machine learning solutions on AWS.

Required Experience

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

• 5-10 Years of Experience: In data science or related fields, with a proven track record of handling complex data projects.

• Project Leadership: Experience in leading data science projects and teams, with a focus on delivering business value.

• Domain Expertise: Experience in a specific industry, such as finance, healthcare, or technology, can be highly beneficial.

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