Salary for Executive-level / Director Data Manager during 2023

Salary details

The average executive-level / director Data Manager salary lies between USD 72,000 and USD 80,000 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 Executive-level / Director Data Manager roles

The three most common job tag items assiciated with executive-level / director Data Manager job listings are Data management, SQL and Excel. 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:

Data management | 10 jobs SQL | 9 jobs Excel | 9 jobs Python | 7 jobs Tableau | 7 jobs Data analysis | 6 jobs Research | 5 jobs Statistics | 5 jobs AWS | 4 jobs APIs | 4 jobs Mathematics | 4 jobs R | 3 jobs Oracle | 3 jobs Economics | 3 jobs Engineering | 3 jobs Security | 3 jobs Testing | 3 jobs Agile | 3 jobs Privacy | 3 jobs Scala | 2 jobs

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

The three most common job benefits and perks assiciated with executive-level / director Data Manager job listings are Career development, Flex hours 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 | 14 jobs Flex hours | 9 jobs Health care | 9 jobs Startup environment | 8 jobs Team events | 7 jobs Equity / stock options | 5 jobs Parental leave | 5 jobs Flex vacation | 4 jobs Wellness | 4 jobs Competitive pay | 4 jobs Medical leave | 4 jobs Unlimited paid time off | 4 jobs Salary bonus | 2 jobs Lunch / meals | 1 jobs Transparency | 1 jobs Insurance | 1 jobs Flexible spending account | 1 jobs

Salary Composition

The salary for an Executive-level or Director Data Manager 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, the base salary might be higher, but bonuses and stock options can also form a substantial part of the total compensation package. In contrast, companies in smaller markets or industries like healthcare or finance might offer a lower base salary but compensate with higher bonuses or other benefits. Larger companies often provide more comprehensive packages, including retirement plans, health benefits, and other perks, while startups might offer equity as a significant part of the compensation.

Increasing Salary

To increase your salary from this position, consider pursuing further specialization or leadership roles. This could involve taking on more strategic responsibilities, such as overseeing larger teams or managing cross-functional projects. Networking within the industry and building a strong personal brand can also open up opportunities for higher-paying roles. Additionally, staying updated with the latest trends and technologies in AI/ML can make you more valuable to your current or potential employers. Seeking roles in high-demand industries or regions can also lead to better compensation packages.

Educational Requirements

Most Executive-level or Director Data Manager positions require at least a bachelor's degree in a relevant field such as computer science, data science, statistics, or engineering. However, a master's degree or even a Ph.D. is often preferred, especially for roles that demand a deep understanding of AI/ML technologies. Business administration degrees, such as an MBA, can also be beneficial, particularly for roles that involve significant management responsibilities.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate your expertise. Certifications such as Certified Analytics Professional (CAP), Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer can be valuable. These certifications show a commitment to the field and a recognized level of competence, which can be attractive to employers.

Required Experience

Typically, these roles require extensive experience in data science, AI, or related fields. This often means at least 7-10 years of experience, with several years in a managerial or leadership position. Experience in leading data-driven projects, managing teams, and developing data strategies is crucial. A proven track record of successful project delivery and the ability to drive business outcomes through data insights is highly valued.

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