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

Salary details

The average senior-level / expert Data Manager salary lies between USD 110,400 and USD 145,000 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. 22, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Manager roles

The three most common job tag items assiciated with senior-level / expert Data Manager job listings are Data management, Testing and Research. 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 | 111 jobs Testing | 65 jobs Research | 59 jobs Excel | 51 jobs Security | 45 jobs Architecture | 44 jobs Engineering | 31 jobs Computer Science | 30 jobs Oracle | 26 jobs SQL | 26 jobs Data quality | 26 jobs Biology | 25 jobs Statistics | 21 jobs Privacy | 20 jobs Agile | 18 jobs Data analysis | 18 jobs R | 17 jobs Data governance | 17 jobs Finance | 15 jobs GCP | 15 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Manager roles

The three most common job benefits and perks assiciated with senior-level / expert Data Manager job listings are Career development, Health care and Competitive pay. 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 | 105 jobs Health care | 56 jobs Competitive pay | 41 jobs Startup environment | 38 jobs Flex vacation | 27 jobs Flex hours | 25 jobs Insurance | 23 jobs Equity / stock options | 18 jobs 401(k) matching | 14 jobs Team events | 14 jobs Salary bonus | 10 jobs Wellness | 7 jobs Parental leave | 6 jobs Travel | 6 jobs Medical leave | 6 jobs Gear | 5 jobs Home office stipend | 4 jobs Fitness / gym | 3 jobs Unlimited paid time off | 3 jobs Conferences | 2 jobs

Salary Composition for Senior-Level/Expert Data Manager Roles

In the United States, the salary composition for a Senior-level or Expert Data Manager in AI/ML/Data Science typically includes a combination of a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The base salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Performance bonuses can vary significantly depending on the company and industry, often ranging from 10% to 20% of the total compensation. Additional remuneration, such as stock options, is more common in tech companies and startups, potentially making up 5% to 15% of the total package.

Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job markets. Industry-wise, tech and finance sectors often offer higher compensation compared to healthcare or education. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and bonuses.

Steps to Increase Salary from a Senior-Level Position

To increase your salary further from a Senior-level Data Manager position, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within AI/ML, such as deep learning, natural language processing, or AI ethics, which are in high demand and can command higher salaries.
• Pursue Leadership Roles: Transition into roles that involve leading teams or projects, such as a Director of Data Science or Chief Data Officer, which typically offer higher compensation.
• Expand Your Network: Engage with industry professionals through conferences, workshops, and online platforms to increase your visibility and open up new opportunities.
• Negotiate Effectively: When offered a new position or during performance reviews, negotiate for higher pay by highlighting your achievements and the value you bring to the organization.
• Consider Relocation: If feasible, consider relocating to regions with higher salary averages for your role.

Educational Requirements for Senior-Level Data Manager Roles

Most Senior-level Data Manager positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Mathematics. However, a master's degree or Ph.D. is often preferred, especially for roles in research-intensive industries or academia. Advanced degrees provide a deeper understanding of complex data systems and methodologies, which are crucial for high-level decision-making and strategy development.

Helpful Certifications for Data Managers

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Data Engineer: Focuses on designing, building, and operationalizing data processing systems.
• AWS Certified Big Data – Specialty: Demonstrates expertise in using AWS data services.
• Microsoft Certified: Azure Data Scientist Associate: Validates skills in applying Azure's machine learning techniques.

Experience Required for Senior-Level Data Manager Roles

Typically, a Senior-level Data Manager is expected to have at least 7-10 years of experience in data management, analytics, or a related field. This experience should include a proven track record of managing data projects, leading teams, and implementing data-driven strategies. Experience in specific industries or with certain technologies can also be advantageous, depending on the job requirements.

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