Salary for Senior-level / Expert Data Lead in United States during 2023

Salary details

The average senior-level / expert Data Lead salary lies between USD 80,000 and USD 225,000 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: Dec. 29, 2024

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 SQL, Engineering and Data management. 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:

SQL | 17 jobs Engineering | 17 jobs Data management | 13 jobs Architecture | 10 jobs Data strategy | 10 jobs Pipelines | 10 jobs Machine Learning | 9 jobs Power BI | 8 jobs Data governance | 8 jobs Data quality | 8 jobs ETL | 7 jobs Finance | 7 jobs Security | 7 jobs Snowflake | 7 jobs Computer Science | 7 jobs Python | 6 jobs BigQuery | 6 jobs Data pipelines | 6 jobs Excel | 6 jobs Tableau | 5 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, Flex vacation and Flex hours. 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 | 14 jobs Flex vacation | 11 jobs Flex hours | 9 jobs Startup environment | 9 jobs Parental leave | 8 jobs Health care | 8 jobs Equity / stock options | 6 jobs Home office stipend | 6 jobs Insurance | 5 jobs Salary bonus | 4 jobs Team events | 3 jobs Gear | 2 jobs Competitive pay | 2 jobs 401(k) matching | 1 jobs Wellness | 1 jobs Conferences | 1 jobs Snacks / Drinks | 1 jobs Medical leave | 1 jobs Pet friendly | 1 jobs Unlimited paid time off | 1 jobs

Salary Composition

In the United States, the salary for a Senior-level or Expert Data Lead in AI/ML/Data Science typically comprises a base salary, performance 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 60% to 80%. Performance bonuses can vary significantly, often between 10% to 20% of the base salary, depending on individual and company performance. Additional remuneration, such as stock options, can be a significant part of the package, particularly in startups or large tech firms, and may account for 10% to 30% of the total compensation. The composition can vary by region, with tech hubs like Silicon Valley offering higher equity components, while regions with a lower cost of living might offer higher base salaries. Industry also plays a role; for instance, finance and healthcare may offer higher base salaries, while tech companies might provide more in stock options. Company size can influence the package, with larger companies often providing more comprehensive benefits and bonuses.

Increasing Salary Further

To increase your salary beyond the current median, consider pursuing leadership roles that expand your responsibilities, such as a Director of Data Science or Chief Data Officer. Developing expertise in emerging technologies like AI ethics, quantum computing, or advanced machine learning techniques can also make you more valuable. Networking within industry circles and attending conferences can open opportunities for higher-paying roles. Additionally, negotiating your salary based on market research and leveraging offers from other companies can be effective strategies. Pursuing an MBA or executive education programs can also enhance your leadership skills and make you a more attractive candidate for higher-paying positions.

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. is often preferred, especially for roles that involve research or advanced algorithm development. Candidates with a strong academic background in machine learning, artificial intelligence, or data analytics are highly sought after. Additionally, coursework or experience in business management can be beneficial for roles that require strategic decision-making and team leadership.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Certifications such as the Certified Analytics Professional (CAP), TensorFlow Developer Certificate, or AWS Certified Machine Learning – Specialty can be valuable. Additionally, certifications in data management and governance, such as the Certified Information Management Professional (CIMP), can be beneficial for roles that involve overseeing data strategy and compliance.

Required Experience

Typically, a Senior-level or Expert Data Lead role requires at least 8 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 projects, managing teams, and delivering business value through data-driven insights. Experience in a specific industry, such as finance, healthcare, or technology, can be advantageous, as it provides domain-specific knowledge that can be critical for certain roles.

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