Salary for Senior-level / Expert Data Lead in United States during 2024

Salary details

The average senior-level / expert Data Lead salary lies between USD 114,720 and USD 180,000 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: Jan. 19, 2025

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Lead job listings are Data management, Data quality and SQL. 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:

Data management | 125 jobs Data quality | 103 jobs SQL | 99 jobs Engineering | 96 jobs Data governance | 96 jobs Architecture | 77 jobs Python | 66 jobs Research | 64 jobs Security | 59 jobs Data analysis | 58 jobs Computer Science | 56 jobs Finance | 52 jobs Data strategy | 52 jobs Agile | 51 jobs Power BI | 50 jobs Testing | 50 jobs ETL | 49 jobs Data Analytics | 48 jobs Tableau | 47 jobs Excel | 45 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Lead job listings are Career development, Health care and Flex hours. 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 | 146 jobs Health care | 80 jobs Flex hours | 73 jobs Startup environment | 67 jobs Competitive pay | 62 jobs Team events | 43 jobs Equity / stock options | 39 jobs Parental leave | 38 jobs Insurance | 37 jobs Salary bonus | 30 jobs Medical leave | 27 jobs Wellness | 23 jobs Flex vacation | 19 jobs Fitness / gym | 17 jobs Home office stipend | 13 jobs 401(k) matching | 12 jobs Transparency | 12 jobs Unlimited paid time off | 8 jobs Gear | 6 jobs Snacks / Drinks | 6 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Lead in AI/ML/Data Science typically includes a combination of a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can significantly increase the total compensation, sometimes by 10% to 30% or more. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market.

Increasing Salary Further

To increase your salary beyond the median of USD 140,000, consider the following strategies:

• Specialization: Develop expertise in niche areas of AI/ML, such as deep learning, natural language processing, or computer vision, which are in high demand.
• Leadership Skills: Enhance your leadership and management skills to qualify for higher-level positions such as Director of Data Science or Chief Data Officer.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and valuable to employers.
• Negotiation: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

Most Senior-level or Expert Data Lead positions require at least a master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. A Ph.D. can be advantageous, especially for roles that involve research or advanced technical challenges. Employers often look for candidates with a strong foundation in quantitative and analytical skills, as well as a deep understanding of machine learning algorithms and data analysis techniques.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

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

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

Required Experience

Typically, a Senior-level or Expert Data Lead role requires at least 7 to 10 years of experience in data science, machine learning, or a related field. This experience should include a proven track record of leading data-driven projects, managing teams, and delivering impactful results. Experience in a specific industry, such as finance, healthcare, or technology, can also be beneficial, as it provides domain knowledge that can be critical for certain roles.

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