Salary for Senior-level / Expert Data Product Manager during 2024

Salary details

The average senior-level / expert Data Product Manager salary lies between USD 141,158 and USD 200,000 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: Dec. 22, 2024

Salary trend

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

The three most common job tag items assiciated with senior-level / expert Data Product Manager job listings are Engineering, SQL and Agile. 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:

Engineering | 83 jobs SQL | 73 jobs Agile | 65 jobs Machine Learning | 49 jobs Architecture | 37 jobs Python | 36 jobs Data governance | 33 jobs Research | 30 jobs Data management | 30 jobs Computer Science | 30 jobs Privacy | 30 jobs Data Analytics | 28 jobs Data analysis | 28 jobs Data quality | 26 jobs Finance | 25 jobs Tableau | 24 jobs Snowflake | 24 jobs Excel | 24 jobs R | 22 jobs ETL | 22 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Product Manager job listings are Career development, Health care and Flex hours. 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 | 89 jobs Health care | 62 jobs Flex hours | 44 jobs Competitive pay | 44 jobs Equity / stock options | 41 jobs Startup environment | 41 jobs Team events | 37 jobs Salary bonus | 36 jobs Insurance | 31 jobs Flex vacation | 28 jobs Parental leave | 22 jobs Medical leave | 22 jobs 401(k) matching | 19 jobs Home office stipend | 13 jobs Wellness | 12 jobs Transparency | 8 jobs Flexible spending account | 8 jobs Gear | 7 jobs Relocation support | 5 jobs Snacks / Drinks | 5 jobs

Salary Composition

The salary composition for a Senior-level or Expert Data Product Manager in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity. The base salary is often the largest component, making up about 60-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10-20%. Additional remuneration, such as stock options or equity, can vary significantly depending on the company size and industry, ranging from 10-20% or more. In tech hubs like Silicon Valley, equity can be a substantial part of the package, whereas in other regions, the focus might be more on cash compensation. Larger companies often offer more structured bonus plans and equity, while startups might offer higher equity stakes in lieu of a higher base salary.

Increasing Salary Further

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and data science methodologies. Specializing in a niche area can make you more valuable.
• Leadership Roles: Aim for leadership positions such as Head of Data Products or Chief Data Officer, which come with higher compensation.
• Industry Transition: Moving to a high-paying industry like finance or healthcare can result in a significant salary increase.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into salary trends.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level Data Product Manager roles require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Engineering, or Business. However, a master's degree or an MBA is often preferred, especially for roles that require a deep understanding of both technical and business aspects. Advanced degrees can provide a competitive edge and are sometimes necessary for roles in top-tier companies or specialized industries.

Helpful Certificates

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

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Project Management Professional (PMP): Useful for managing complex data projects.
• AWS Certified Machine Learning – Specialty: Demonstrates expertise in machine learning on the AWS platform.
• Google Professional Data Engineer: Shows proficiency in designing and managing data solutions on Google Cloud.

Required Experience

Typically, a Senior-level Data Product Manager is expected to have 7-10 years of experience in data science, product management, or a related field. This experience should include a proven track record of managing data-driven products, leading cross-functional teams, and delivering successful projects. Experience in AI/ML is crucial, as is familiarity with data analytics tools and platforms.

Related salaries

Want to contribute?