Salary for Senior-level / Expert Data Manager during 2024

Salary details

The average senior-level / expert Data Manager salary lies between USD 80,000 and USD 133,500 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: 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

The salary for a Senior-level or Expert Data Manager in AI/ML/Data Science typically comprises a fixed base salary, performance bonuses, and additional remuneration such as stock options or profit-sharing. The fixed base salary is often the largest component, accounting for 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, usually ranging from 10-20% of the total salary. Additional remuneration, such as stock options, is more common in tech companies and startups, potentially making up 5-10% of the total package.

Regional differences also play a significant role. For instance, salaries in tech hubs like San Francisco or New York are generally higher due to the cost of living and demand for talent. Industry-wise, tech companies and financial services tend to offer higher compensation compared to sectors like healthcare or education. Company size can also influence salary composition, with larger companies often providing more comprehensive benefits and bonuses.

Increasing Salary Further

To increase your salary beyond the median of USD 113,000, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML, such as natural language processing or computer vision, which can command higher salaries.
• Leadership Roles: Transition into roles with more managerial responsibilities, such as Head of Data Science or Chief Data Officer.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive.
• 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 in research-intensive industries or academia. Advanced degrees provide a deeper understanding of complex algorithms and data analysis techniques, which are crucial for high-level decision-making and strategy development.

Helpful Certifications

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing and building machine learning models on Google Cloud.
• AWS Certified Machine Learning – Specialty: Shows expertise in implementing machine learning solutions on the AWS platform.
• Microsoft Certified: Azure AI Engineer Associate: Highlights skills in using Azure AI services to build and integrate AI solutions.

Required Experience

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

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