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

Salary details

The average senior-level / expert Data Product Owner salary lies between USD 110,000 and USD 131,000 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: Nov. 10, 2024

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

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

Agile | 31 jobs Engineering | 26 jobs Data management | 22 jobs Scrum | 17 jobs Data quality | 17 jobs SQL | 16 jobs Computer Science | 16 jobs Python | 13 jobs Data analysis | 13 jobs Data strategy | 12 jobs Machine Learning | 11 jobs Data Analytics | 11 jobs Finance | 11 jobs Data governance | 11 jobs Statistics | 9 jobs Research | 8 jobs Security | 8 jobs Architecture | 8 jobs Data visualization | 8 jobs Tableau | 7 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Product Owner 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 2024 and the number of open jobs that where offering them during that period:

Career development | 24 jobs Health care | 15 jobs Competitive pay | 15 jobs Flex hours | 12 jobs Salary bonus | 12 jobs Equity / stock options | 10 jobs 401(k) matching | 9 jobs Wellness | 8 jobs Startup environment | 8 jobs Insurance | 8 jobs Flex vacation | 7 jobs Team events | 7 jobs Parental leave | 5 jobs Transparency | 2 jobs Relocation support | 2 jobs Medical leave | 2 jobs Home office stipend | 2 jobs

Salary Composition

The salary for a Senior-level or Expert Data Product Owner in AI/ML/Data Science typically comprises a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The fixed base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Bonuses can vary significantly depending on the company's performance and individual achievements, usually accounting for 10% to 20% of the total salary. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 10% to 20%.

Regional differences play a significant role in salary composition. For instance, tech hubs like Silicon Valley or New York City may offer higher base salaries and more lucrative stock options compared to other regions. Industry also impacts salary composition; tech companies might offer more in stock options, while financial services might provide higher bonuses. Company size can influence the package as well, with larger companies often providing more comprehensive benefits and smaller startups offering more equity.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and data science methodologies. Specializing in niche areas can make you more valuable.
• Leadership Roles: Transition into leadership roles such as Head of Data Products or Chief Data Officer, which typically come with higher compensation.
• Industry Change: Moving to a higher-paying industry, such as finance or healthcare, can result in a 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 Owner 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 an MBA can be highly advantageous, especially for roles that require a strong understanding of business strategy and data-driven decision-making. Advanced degrees can also help differentiate candidates in a competitive job market.

Helpful Certifications

While not always mandatory, certain certifications can enhance your qualifications and demonstrate 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 proficiency in deploying machine learning models on AWS.
• Google Professional Data Engineer: Shows expertise in designing and managing data processing systems.

Required Experience

Typically, a Senior-level Data Product Owner should have 7-10 years of experience in data science, machine learning, or a related field. This experience should include a proven track record of managing data products, leading cross-functional teams, and delivering data-driven solutions. Experience in product management and a deep understanding of the industry in which you are applying are also crucial.

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