Salary for Executive-level / Director Head of Data during 2023

Salary details

The average executive-level / director Head of Data salary lies between USD 142,200 and USD 269,600 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. 24, 2024

Salary trend

Top 20 Job Tags for Executive-level / Director Head of Data roles

The three most common job tag items assiciated with executive-level / director Head of Data job listings are Engineering, Machine Learning and Data strategy. 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:

Engineering | 77 jobs Machine Learning | 62 jobs Data strategy | 51 jobs Python | 48 jobs SQL | 47 jobs Architecture | 42 jobs Computer Science | 39 jobs Data governance | 38 jobs Data Analytics | 37 jobs Statistics | 36 jobs Data management | 32 jobs AWS | 30 jobs Tableau | 29 jobs Security | 29 jobs Finance | 28 jobs Data quality | 28 jobs Agile | 27 jobs R | 23 jobs DataOps | 23 jobs Privacy | 23 jobs

Top 20 Job Perks/Benefits for Executive-level / Director Head of Data roles

The three most common job benefits and perks assiciated with executive-level / director Head of Data job listings are Career development, Startup environment and Health care. 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 | 107 jobs Startup environment | 65 jobs Health care | 57 jobs Flex hours | 55 jobs Equity / stock options | 43 jobs Team events | 37 jobs Flex vacation | 34 jobs Insurance | 32 jobs Parental leave | 26 jobs Competitive pay | 25 jobs Salary bonus | 25 jobs Wellness | 20 jobs Medical leave | 13 jobs Home office stipend | 12 jobs Gear | 8 jobs Conferences | 8 jobs Unlimited paid time off | 8 jobs Signing bonus | 7 jobs 401(k) matching | 5 jobs Flexible spending account | 5 jobs

Salary Composition

The salary for an Executive-level or Director Head of Data position typically comprises a mix of fixed salary, bonuses, and additional remuneration such as stock options or equity. The fixed salary often forms the bulk of the compensation package, but the proportion can vary significantly based on region, industry, and company size. In tech hubs like Silicon Valley, a larger portion of the compensation might come from stock options, reflecting the high-growth potential of companies in that area. In contrast, traditional industries might offer a higher fixed salary with smaller bonuses. Bonuses are usually performance-based and can be tied to individual, team, or company performance metrics. Additional remuneration might include benefits such as health insurance, retirement plans, and other perks like relocation assistance or professional development funds.

Increasing Salary

To increase your salary from this position, consider the following strategies:

• Expand Your Skill Set: Acquiring new skills, especially in emerging technologies or methodologies, can make you more valuable to your organization or attractive to other employers.
• Network and Build Relationships: Networking with other professionals in your field can open up opportunities for higher-paying roles or consulting gigs.
• Seek Leadership Opportunities: Taking on more responsibility or leading larger teams can justify a higher salary.
• Negotiate Effectively: When discussing compensation, be prepared with data on industry standards and your contributions to the company.
• Consider Relocation: Some regions offer higher salaries due to cost of living or demand for talent.

Educational Requirements

Most executive-level positions in AI/ML/Data Science require at least a master's degree in a relevant field such as Computer Science, Data Science, Statistics, or Business Administration. A Ph.D. can be advantageous, especially in research-intensive roles or industries. Additionally, a strong foundation in mathematics, statistics, and computer programming is essential.

Helpful Certifications

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

• Certified Analytics Professional (CAP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Data Science Council of America (DASCA) Senior Data Scientist

These certifications can help validate your skills and knowledge in specific areas of AI/ML and data science.

Required Experience

Typically, candidates for this role have extensive experience, often 10+ years, in data science, analytics, or a related field. This experience should include a proven track record of leading data-driven projects, managing teams, and delivering business value through data insights. Experience in strategic planning and execution, as well as a deep understanding of industry-specific challenges and opportunities, is also crucial.

Related salaries

Want to contribute?