Salary for Executive-level / Director Data Manager in United States during 2023

Salary details

The average executive-level / director Data Manager salary lies between USD 70,000 and USD 80,000 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: 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

In the United States, the salary composition for an Executive-level or Director Data Manager in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 60% to 80% of the total compensation package. Bonuses, which can be performance-based or company-wide, might account for 10% to 20%. Additional remuneration, such as stock options, profit sharing, or other incentives, can vary significantly depending on the company size and industry. For instance, tech giants and startups in regions like Silicon Valley might offer substantial equity, while companies in other regions or industries might focus more on cash bonuses.

Steps to Increase Salary

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

• Skill Enhancement: Continuously update your technical and managerial skills. Specializing in emerging technologies or methodologies can make you more valuable.
• Networking: Build a strong professional network. Engaging with industry leaders and attending conferences can open up higher-paying opportunities.
• Performance Excellence: Demonstrate exceptional performance and leadership in your current role. This can lead to promotions or salary negotiations.
• Industry Transition: Consider moving to industries with higher pay scales for data roles, such as finance or healthcare.
• Geographic Mobility: Be open to relocating to regions with higher salary benchmarks for your role.

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 in top-tier companies or those involving complex data strategies. An MBA can also be beneficial, particularly for roles with a strong focus on business strategy and leadership.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• 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 validate your skills and knowledge, making you a more competitive candidate.

Required Experience

Typically, this role requires significant experience, often 8-10 years, in data science, analytics, or a related field. Experience in managing teams, leading projects, and developing data-driven strategies is crucial. Prior roles should demonstrate a progression of responsibility and impact, ideally including experience in both technical and managerial capacities.

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