Salary for Senior-level / Expert Data Manager in United States during 2024

Salary details

The average senior-level / expert Data Manager salary lies between USD 89,700 and USD 140,000 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, Research and Testing. 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 | 285 jobs Research | 166 jobs Testing | 143 jobs Statistics | 131 jobs Excel | 125 jobs SAS | 111 jobs CDISC | 107 jobs Privacy | 101 jobs Data quality | 92 jobs Pharma | 78 jobs Engineering | 73 jobs SQL | 65 jobs Security | 65 jobs GCP | 57 jobs Data governance | 47 jobs Computer Science | 45 jobs Data analysis | 43 jobs R | 41 jobs Architecture | 34 jobs Consulting | 31 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, Team events and Health care. 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 | 200 jobs Team events | 120 jobs Health care | 118 jobs Flex hours | 78 jobs Insurance | 58 jobs Medical leave | 57 jobs Startup environment | 56 jobs Parental leave | 50 jobs Competitive pay | 49 jobs Salary bonus | 44 jobs Equity / stock options | 38 jobs Flex vacation | 38 jobs 401(k) matching | 26 jobs Wellness | 20 jobs Relocation support | 13 jobs Travel | 12 jobs Conferences | 11 jobs Gear | 10 jobs Home office stipend | 7 jobs Transparency | 6 jobs

Salary Composition

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 equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total compensation, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, is more common in larger 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 companies, finance, and healthcare often offer higher compensation compared to academia or non-profit sectors. Company size can also influence salary composition, with larger companies typically offering more comprehensive benefits and stock options.

Increasing Salary

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

• Specialization: Develop expertise in a niche area within AI/ML, such as natural language processing or computer vision, which can command higher salaries.
• Leadership Roles: Transition into leadership roles such as Director of Data Science or Chief Data Officer, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to enhance your skill set and marketability.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during job offers or performance reviews.

Educational Requirements

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 that involve complex data analysis and strategic decision-making. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical methods, and data management techniques, which are crucial for this role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise in AI/ML and data management. Some valuable certifications include:

• Certified Data Management Professional (CDMP)
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• SAS Certified AI & Machine Learning Professional

These certifications can help validate your skills and knowledge, making you a more attractive candidate for senior roles.

Required Experience

Typically, a Senior-level Data Manager position requires at least 7 to 10 years of experience in data science, machine learning, or a related field. This experience should include a proven track record of managing data projects, leading teams, and delivering data-driven insights that impact business decisions. Experience in specific industries or with certain technologies can also be advantageous, depending on the job requirements.

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