Salary for Senior-level / Expert Product Manager in United States during 2024
💰 The median Salary for Senior-level / Expert Product Manager in United States during 2024 is USD 194,000
✏️ This salary info is based on 422 individual salaries reported during 2024
Salary details
The average senior-level / expert Product Manager salary lies between USD 148,000 and USD 252,000 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.
- Job title
- Product Manager
- Experience
- Senior-level / Expert
- Region
- United States
- Salary year
- 2024
- Sample size
- 422
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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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:Top 20 Job Tags for Senior-level / Expert Product Manager roles
The three most common job tag items assiciated with senior-level / expert Product Manager job listings are Engineering, Machine Learning and Research. 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 | 707 jobs Machine Learning | 574 jobs Research | 396 jobs Computer Science | 343 jobs Agile | 296 jobs Generative AI | 259 jobs SQL | 220 jobs LLMs | 188 jobs Privacy | 181 jobs Python | 168 jobs Security | 154 jobs Testing | 154 jobs Architecture | 152 jobs Data Analytics | 133 jobs UX | 131 jobs Data analysis | 130 jobs ML models | 128 jobs Market research | 116 jobs KPIs | 114 jobs Finance | 102 jobsTop 20 Job Perks/Benefits for Senior-level / Expert Product Manager roles
The three most common job benefits and perks assiciated with senior-level / expert Product Manager job listings are Career development, Health care and Equity / stock options. 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 | 674 jobs Health care | 421 jobs Equity / stock options | 418 jobs Competitive pay | 325 jobs Startup environment | 300 jobs Flex hours | 287 jobs Salary bonus | 268 jobs Flex vacation | 219 jobs Medical leave | 211 jobs Insurance | 211 jobs Team events | 202 jobs Parental leave | 181 jobs 401(k) matching | 144 jobs Wellness | 132 jobs Home office stipend | 61 jobs Unlimited paid time off | 59 jobs Transparency | 57 jobs Flexible spending account | 57 jobs Fitness / gym | 50 jobs Conferences | 36 jobsSalary Composition for Senior-level/Expert Product Manager in AI/ML/Data Science
In the United States, the salary for a Senior-level or Expert 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 largest portion, ranging from 60% to 80% of the total compensation package. Performance bonuses can vary significantly, often between 10% to 20%, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, can make up the remaining 10% to 20%, and this is more prevalent in larger tech companies or startups with high growth potential. 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 base salary proportion. Industry and company size also play a role; larger companies might offer more structured bonus plans, while startups might provide more equity.
Steps to Increase Salary from This Position
To increase your salary beyond the median of USD 194,000, consider the following strategies:
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Skill Enhancement: Continuously update your skills in AI/ML technologies and product management methodologies. This could involve learning new programming languages, understanding emerging AI trends, or mastering advanced data analytics tools.
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Leadership Roles: Seek opportunities to lead larger teams or more complex projects. Demonstrating leadership in high-impact projects can position you for promotions or salary negotiations.
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Networking and Industry Engagement: Engage with industry events, conferences, and professional groups. Networking can open doors to higher-paying opportunities and provide insights into industry salary trends.
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Negotiation Skills: Improve your negotiation skills to better advocate for salary increases during performance reviews or when transitioning to new roles.
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Advanced Education: Consider pursuing an MBA or a specialized master's degree in AI/ML, which can enhance your qualifications and justify a higher salary.
Educational Requirements
Most Senior-level or Expert Product Manager roles in AI/ML/Data Science require at least a bachelor's degree in a relevant field such as Computer Science, Engineering, Data Science, or Business Administration. However, a master's degree or an MBA is often preferred, especially for senior positions. These advanced degrees can provide a deeper understanding of both technical and business aspects, which is crucial for product management in AI/ML.
Helpful Certifications
While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some valuable certifications include:
- Certified Scrum Product Owner (CSPO): Useful for understanding agile product management.
- Project Management Professional (PMP): Recognized for project management skills.
- AWS Certified Machine Learning – Specialty: Demonstrates expertise in machine learning on the AWS platform.
- Google Cloud Professional Data Engineer: Validates skills in designing and building data processing systems.
Experience Requirements
Typically, a Senior-level or Expert Product Manager in AI/ML/Data Science is expected to have 7-10 years of experience in product management or related fields. This experience should include a strong track record of managing successful products, preferably in the tech industry, and a deep understanding of AI/ML technologies. Experience in leading cross-functional teams and working in agile environments is also highly valued.
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