Salary for Mid-level / Intermediate Data Product Owner in United States during 2024

Salary details

The average mid-level / intermediate Data Product Owner salary lies between USD 97,000 and USD 156,000 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

Top 20 Job Tags for Mid-level / Intermediate Data Product Owner roles

The three most common job tag items assiciated with mid-level / intermediate Data Product Owner job listings are Agile, Engineering and SQL. 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 | 36 jobs Engineering | 23 jobs SQL | 19 jobs Scrum | 15 jobs Computer Science | 15 jobs Jira | 14 jobs Architecture | 12 jobs Excel | 12 jobs Data quality | 11 jobs Data analysis | 10 jobs ETL | 9 jobs Finance | 9 jobs Data management | 9 jobs Data governance | 9 jobs Banking | 8 jobs Power BI | 8 jobs Privacy | 8 jobs Machine Learning | 7 jobs Security | 7 jobs CX | 7 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Data Product Owner roles

The three most common job benefits and perks assiciated with mid-level / intermediate Data Product Owner job listings are Career development, Competitive pay 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 | 22 jobs Competitive pay | 13 jobs Health care | 12 jobs Flex hours | 11 jobs Startup environment | 10 jobs Team events | 8 jobs Insurance | 6 jobs Salary bonus | 5 jobs Flex vacation | 3 jobs Equity / stock options | 2 jobs Parental leave | 2 jobs Fitness / gym | 2 jobs 401(k) matching | 1 jobs Wellness | 1 jobs Transparency | 1 jobs Conferences | 1 jobs Yoga | 1 jobs Medical leave | 1 jobs Home office stipend | 1 jobs

Salary Composition

The salary for a Mid-level Data Product Owner in the AI/ML/Data Science field typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include stock options, especially in tech companies or startups, and benefits like health insurance, retirement plans, and professional development allowances. The composition can vary by region, with tech hubs like Silicon Valley offering higher base salaries and stock options, while other regions might offer more balanced packages. Industry and company size also play a role; larger companies might offer more comprehensive benefits, while startups might compensate with equity.

Increasing Salary

To increase your salary from this position, consider pursuing advanced roles such as Senior Data Product Owner or transitioning into a managerial position like Data Product Manager. Gaining expertise in emerging technologies and methodologies in AI/ML can make you more valuable. Networking within the industry and seeking mentorship can provide insights into higher-paying opportunities. Additionally, obtaining advanced certifications or a master's degree in a related field can enhance your qualifications. Demonstrating leadership skills and a track record of successful product launches can also position you for salary negotiations or promotions.

Educational Requirements

Most Mid-level Data Product Owner positions require a bachelor's degree in a relevant field such as Computer Science, Data Science, Business Administration, or Engineering. Some roles may prefer candidates with a master's degree, especially in competitive markets or for positions with a strong technical focus. A solid understanding of data analytics, machine learning principles, and product management is essential. Courses in statistics, programming, and business strategy can be particularly beneficial.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise. Commonly beneficial certifications include:

• Certified Scrum Product Owner (CSPO) for agile product management skills.
• Google Data Analytics Professional Certificate for foundational data skills.
• AWS Certified Machine Learning – Specialty for cloud-based machine learning expertise.
• Data Science certifications from platforms like Coursera or edX, which offer courses from universities like Stanford or MIT.

These certifications can provide a competitive edge and signal commitment to professional development.

Required Experience

Typically, a Mid-level Data Product Owner should have 3-5 years of experience in data-related roles, such as data analysis, data engineering, or product management. Experience in managing data-driven projects and collaborating with cross-functional teams is crucial. Familiarity with agile methodologies and experience in the AI/ML domain can be particularly advantageous. Demonstrated success in launching data products or features and a strong understanding of the product lifecycle are often required.

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