Salary for Senior-level / Expert Data Product Manager in United States during 2023

Salary details

The average senior-level / expert Data Product Manager salary lies between USD 120,000 and USD 151,000 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: Nov. 17, 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 Machine Learning. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Engineering | 25 jobs SQL | 17 jobs Machine Learning | 14 jobs Research | 12 jobs Data analysis | 11 jobs Big Data | 9 jobs Tableau | 9 jobs Privacy | 9 jobs Testing | 8 jobs Agile | 8 jobs Snowflake | 7 jobs Statistics | 7 jobs Scrum | 6 jobs Data Analytics | 6 jobs E-commerce | 6 jobs Data management | 6 jobs Computer Science | 6 jobs R | 5 jobs Data strategy | 5 jobs Python | 4 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 Health care, Career development and Insurance. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Health care | 17 jobs Career development | 14 jobs Insurance | 11 jobs Flex vacation | 9 jobs Competitive pay | 9 jobs Flex hours | 7 jobs Transparency | 7 jobs Team events | 7 jobs Equity / stock options | 6 jobs Startup environment | 6 jobs Home office stipend | 5 jobs 401(k) matching | 4 jobs Parental leave | 4 jobs Wellness | 4 jobs Fitness / gym | 3 jobs Salary bonus | 3 jobs Medical leave | 2 jobs Unlimited paid time off | 2 jobs Travel | 1 jobs Gear | 1 jobs

Salary Composition

In the United States, 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 often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or tied to company success, usually account for 10% to 20%. Additional remuneration, such as stock options or equity, can vary significantly depending on the company size and industry. For instance, tech giants and startups in Silicon Valley might offer substantial equity packages, while companies in other regions or industries might provide smaller equity components or other benefits like profit-sharing.

Increasing Salary

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

• Specialize in High-Demand Areas: Focus on emerging technologies or niche areas within AI/ML that are in high demand but have a limited talent pool.
• Leadership Roles: Transition into leadership roles such as Head of Data Products or Chief Data Officer, which typically offer higher compensation.
• Negotiation Skills: Enhance your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.
• Continuous Learning: Stay updated with the latest trends and technologies in AI/ML to maintain your competitive edge and justify salary increases.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into industry salary standards.

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 involve strategic decision-making and leadership. Advanced degrees can provide a deeper understanding of technical concepts and business acumen, which are crucial for managing complex data products.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credibility and demonstrate your expertise in the field. Some valuable certifications include:

• Certified Analytics Professional (CAP)
• Google Professional Data Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• PMI Agile Certified Practitioner (PMI-ACP)

These certifications can help you stand out in a competitive job market and may lead to better job opportunities and higher salaries.

Required Experience

Typically, a Senior-level Data Product Manager is expected to have 7 to 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 projects, understanding of data infrastructure, and familiarity with data analytics tools are also crucial.

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