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

Salary details

The average senior-level / expert Data Product Manager salary lies between USD 120,000 and USD 151,000 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. 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

The salary for a Senior-level or Expert Data Product Manager in AI/ML/Data Science typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 60% to 80%. Performance bonuses can vary significantly, often between 10% to 20% of the base salary, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, can be a significant part of the package in startups or large tech firms, potentially making up 10% to 30% of the total compensation. The composition can vary by region, with tech hubs like Silicon Valley offering higher equity components, while regions with a lower cost of living might offer a higher percentage of fixed salary. Industry and company size also play a role, with larger companies often providing more structured bonus schemes and smaller startups offering more equity.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in the latest AI/ML technologies and data science methodologies. Specializing in emerging areas like deep learning, natural language processing, or AI ethics 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.
• Networking: Build a strong professional network in the AI/ML community. Attend conferences, participate in webinars, and engage in online forums to increase your visibility and open up new opportunities.
• Industry Transition: Consider transitioning to industries that pay higher salaries for data product managers, such as finance, healthcare, or tech giants.
• Negotiation Skills: 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 Mathematics. However, a master's degree or an MBA can be highly beneficial and is often preferred, especially for senior positions. Advanced degrees can provide a deeper understanding of data analytics, business strategy, and product management, which are crucial for this role.

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 your ability to design, implement, and maintain machine learning solutions on AWS.
• Google Professional Data Engineer: Shows proficiency in designing data processing systems and operationalizing machine learning models.

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 AI/ML projects. Experience in a specific industry can also be beneficial, as it provides domain knowledge that can be crucial for understanding and solving industry-specific challenges.

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