Salary for Senior-level / Expert Data Scientist during 2022

Salary details

The average senior-level / expert Data Scientist salary lies between USD 129,300 and USD 185,900 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: Dec. 15, 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

The salary for a Senior-level or Expert Data Scientist 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 often forms the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses can vary significantly depending on the company's performance and individual contributions, usually accounting for 10% to 20% of the total salary. Additional remuneration, such as stock options, is more common in larger tech firms or startups and can make up 10% to 30% of the total package. Regional differences also play a role; for instance, salaries in the San Francisco Bay Area or New York City tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech and finance sectors often offer higher compensation compared to academia or non-profit organizations.

Increasing Salary

To increase your salary from a 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 or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher salaries.
• Consulting: Explore opportunities in consulting, where you can leverage your expertise across multiple projects and potentially earn more.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and justify salary increments.
• Networking: Engage with professional networks and communities to discover new opportunities and negotiate better compensation packages.

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 research or advanced algorithm development. The educational background should provide a strong foundation in statistical analysis, machine learning, and programming.

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

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

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 highly valued.

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