Salary for Senior-level / Expert Data Lead during 2024

Salary details

The average senior-level / expert Data Lead salary lies between USD 86,666 and USD 163,116 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: Nov. 17, 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 Data management, Data quality and Engineering. 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 | 105 jobs Data quality | 83 jobs Engineering | 81 jobs SQL | 77 jobs Data governance | 75 jobs Architecture | 71 jobs Python | 61 jobs Security | 53 jobs Research | 52 jobs Agile | 51 jobs Data strategy | 48 jobs Finance | 47 jobs Computer Science | 47 jobs Data analysis | 46 jobs Testing | 44 jobs ETL | 41 jobs Power BI | 41 jobs Excel | 40 jobs Data Analytics | 39 jobs Privacy | 38 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 | 133 jobs Health care | 77 jobs Flex hours | 64 jobs Competitive pay | 64 jobs Startup environment | 56 jobs Team events | 41 jobs Equity / stock options | 36 jobs Parental leave | 33 jobs Wellness | 32 jobs Insurance | 31 jobs Salary bonus | 26 jobs Medical leave | 23 jobs Flex vacation | 18 jobs Fitness / gym | 16 jobs Transparency | 13 jobs 401(k) matching | 10 jobs Home office stipend | 9 jobs Snacks / Drinks | 6 jobs Gear | 5 jobs Unlimited paid time off | 5 jobs

Salary Composition

The salary for a Senior-level or Expert Data Lead in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or profit-sharing. The composition can vary significantly depending on the region, industry, and company size. In tech hubs like Silicon Valley or New York, the base salary might be higher, but the cost of living is also elevated. In contrast, companies in smaller cities might offer a lower base salary but compensate with more substantial bonuses or stock options. Industries such as finance or healthcare may offer higher bonuses due to the critical nature of data-driven decision-making in these fields. Larger companies often provide more comprehensive benefits packages, including retirement plans and health insurance, which can add significant value to the overall compensation.

Increasing Salary

To increase your salary further from a Senior-level Data Lead position, consider pursuing leadership roles such as Chief Data Officer (CDO) or Head of Data Science. These roles often come with higher compensation and more strategic responsibilities. Additionally, expanding your expertise in emerging technologies like deep learning, natural language processing, or AI ethics can make you more valuable to employers. Networking within industry-specific conferences and forums can also open doors to higher-paying opportunities. Finally, consider negotiating your salary by leveraging offers from other companies or demonstrating your impact on the company's bottom line through successful projects.

Educational Requirements

Most Senior-level 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 in research-intensive roles or industries that prioritize advanced analytical skills. Employers often look for candidates with a strong foundation in statistical analysis, machine learning algorithms, and data management. Additionally, coursework or experience in business analytics can be beneficial, as it demonstrates the ability to translate data insights into strategic business decisions.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your commitment to professional development. Certifications such as Certified Analytics Professional (CAP), Microsoft Certified: Azure Data Scientist Associate, or Google Professional Data Engineer can be valuable. These certifications validate your skills in data analysis, machine learning, and cloud-based data solutions, making you a more competitive candidate. Additionally, specialized certifications in tools like TensorFlow, PyTorch, or Apache Spark can be advantageous, depending on the technical requirements of the role.

Required Experience

Typically, a Senior-level Data Lead position requires at least 7-10 years of experience in data science or related fields. This experience should include a proven track record of leading data-driven projects, managing teams, and delivering actionable insights that drive business outcomes. Experience in a specific industry can also be beneficial, as it provides context and understanding of industry-specific challenges and data needs. Additionally, experience with big data technologies, cloud platforms, and advanced analytics tools is often required.

Related salaries

Want to contribute?