Salary for Senior-level / Expert Product Manager in United Kingdom during 2024

Salary details

The average senior-level / expert Product Manager salary lies between USD 98,400 and USD 128,125 in the United Kingdom. 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

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 | 728 jobs Machine Learning | 589 jobs Research | 408 jobs Computer Science | 351 jobs Agile | 299 jobs Generative AI | 266 jobs SQL | 224 jobs LLMs | 195 jobs Privacy | 189 jobs Python | 175 jobs Security | 160 jobs Architecture | 159 jobs Testing | 157 jobs Data Analytics | 137 jobs UX | 137 jobs Data analysis | 135 jobs ML models | 133 jobs Market research | 120 jobs KPIs | 117 jobs Finance | 102 jobs

Top 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, Equity / stock options 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 | 694 jobs Equity / stock options | 431 jobs Health care | 431 jobs Competitive pay | 333 jobs Startup environment | 308 jobs Flex hours | 293 jobs Salary bonus | 276 jobs Flex vacation | 225 jobs Medical leave | 216 jobs Insurance | 214 jobs Team events | 205 jobs Parental leave | 185 jobs 401(k) matching | 144 jobs Wellness | 132 jobs Home office stipend | 65 jobs Unlimited paid time off | 62 jobs Transparency | 59 jobs Flexible spending account | 59 jobs Fitness / gym | 50 jobs Conferences | 36 jobs

Salary Composition for Senior-Level/Expert Product Manager in AI/ML/Data Science

In the United Kingdom, the salary for a Senior-level or Expert Product Manager in AI/ML/Data Science typically comprises a fixed base salary, performance-based 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%. Bonuses can vary significantly depending on the company's performance and individual achievements, usually accounting for 10% to 20% of the total package. Additional remuneration, such as stock options, equity, or other benefits, can make up the remaining 10% to 20%.

The composition can vary based on the region, with London-based roles often offering higher base salaries due to the cost of living. Industry also plays a role; tech companies might offer more in stock options, while financial services might provide higher cash bonuses. Company size can influence the package, with larger companies offering more structured bonuses and benefits, while startups might offer more equity.

Steps to Increase Salary from This Position

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

• Skill Enhancement: Continuously update your skills in AI/ML technologies and product management methodologies. This could involve taking advanced courses or certifications in AI/ML or related fields.
• Networking: Build a strong professional network within the AI/ML community. Attend industry conferences, webinars, and workshops to connect with other professionals and stay updated on industry trends.
• Leadership Roles: Seek opportunities to lead larger projects or teams. Demonstrating leadership and the ability to drive significant business outcomes can position you for promotions or salary negotiations.
• Cross-Industry Experience: Gain experience in different industries where AI/ML is applied. This can make you more versatile and valuable, potentially leading to higher-paying opportunities.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level or Expert Product Manager roles in AI/ML/Data Science require a strong educational background. Typically, a bachelor's degree in a relevant field such as Computer Science, Engineering, Mathematics, or Business is essential. Many employers prefer candidates with a master's degree or an MBA, especially if it includes a focus on technology management or data science. Advanced degrees can provide a competitive edge and are often seen as a testament to a candidate's commitment and expertise.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Scrum Product Owner (CSPO): Useful for understanding agile product management.
• Project Management Professional (PMP): Recognized globally, it can be beneficial for managing complex projects.
• AWS Certified Machine Learning – Specialty: Demonstrates expertise in machine learning on the AWS platform.
• Google Cloud Professional Data Engineer: Validates your ability to design, build, and manage data processing systems on Google Cloud.

Required Experience

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 proven track record of managing successful products, preferably in the AI/ML or tech industry. Experience working with cross-functional teams, including engineering, design, and marketing, is crucial. Additionally, hands-on experience with AI/ML technologies or data-driven products is highly valued.

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