Salary for Senior-level / Expert Lead Data Scientist during 2022

Salary details

The average senior-level / expert Lead Data Scientist salary lies between USD 56,723 and USD 172,309 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. 22, 2024

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

The three most common job tag items assiciated with senior-level / expert Lead Data Scientist job listings are Machine Learning, Python 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:

Machine Learning | 59 jobs Python | 54 jobs Statistics | 48 jobs SQL | 41 jobs Engineering | 41 jobs Research | 37 jobs Computer Science | 37 jobs Mathematics | 26 jobs ML models | 25 jobs R | 24 jobs Spark | 22 jobs Testing | 22 jobs AWS | 21 jobs Pipelines | 21 jobs Big Data | 20 jobs Agile | 19 jobs TensorFlow | 18 jobs Scikit-learn | 18 jobs PyTorch | 16 jobs NLP | 15 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Lead Data Scientist job listings are Career development, Team events 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 | 51 jobs Team events | 22 jobs Startup environment | 21 jobs Health care | 20 jobs Flex hours | 18 jobs Flex vacation | 16 jobs Equity / stock options | 15 jobs 401(k) matching | 11 jobs Competitive pay | 10 jobs Insurance | 9 jobs Conferences | 6 jobs Parental leave | 5 jobs Wellness | 5 jobs Salary bonus | 5 jobs Relocation support | 4 jobs Home office stipend | 4 jobs Gear | 3 jobs Medical leave | 3 jobs Flexible spending account | 3 jobs Unlimited paid time off | 3 jobs

Salary Composition

The salary for a Senior-level or Expert Lead 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 composition can vary significantly depending on the region, industry, and company size.

• Region: In the United States, for instance, tech hubs like San Francisco or New York often offer higher base salaries and more substantial equity packages compared to other regions. In Europe, cities like London and Berlin are known for competitive salaries, though they might be slightly lower than their U.S. counterparts.

• Industry: Industries such as finance, healthcare, and technology tend to offer higher compensation packages. In finance, bonuses can be a significant part of the total compensation, sometimes equaling or exceeding the base salary.

• Company Size: Larger companies often provide more structured compensation packages with a mix of salary, bonuses, and stock options. Startups might offer lower base salaries but compensate with significant equity stakes.

Increasing Salary

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

• Specialization: Develop expertise in high-demand areas such as deep learning, natural language processing, or AI ethics. Specializing can make you indispensable and justify a higher salary.

• Leadership Roles: Transition into roles with more responsibility, such as a Data Science Manager or Director of Data Science. These positions often come with higher pay.

• Continuous Learning: Stay updated with the latest technologies and methodologies. Attending workshops, conferences, and pursuing further education can enhance your skills and marketability.

• Networking: Build a strong professional network. Engaging with industry leaders and participating in relevant forums can open up opportunities for higher-paying roles.

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 or are in academia. 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:

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

These certifications demonstrate proficiency in specific tools and platforms, which can be beneficial depending on the company's tech stack.

Required Experience

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:

• Leading data science projects and teams
• Proficiency in programming languages such as Python or R
• Experience with machine learning frameworks like TensorFlow or PyTorch
• Strong analytical and problem-solving skills

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