Product Manager with Geo-Testing/ Marketing Mix Modeling - London hybrid

Required Experience:

• Minimum 5 years of experience in product management, data analytics, or marketing measurement
• Proven knowledge of  Marketing Mix Modeling, Incrementality Testing, and Geo-Testing methodologies
• Hands-on experience working with data science and engineering teams on analytics product development
• Ability to translate complex analytics into actionable business insights

Must-Have Expertise:

• Marketing Mix Modeling (MMM)
• Incrementality Testing
• Geo-Testing

Technologies used in the project:

• Languages/Tools: Python, R, SQL
• Cloud platforms: AWS, GCP, or Azure
• BI / Data Visualization: As needed by the team

Position: Product Manager with  Geo-Testing / Marketing Mix Modeling – London hybrid

Location: London (1 day per week in the office)
Work model: Hybrid (4 days remote, 1 day onsite)
Availability: Only candidates available  ASAP
Recruitment process: 1 stage – interview with the Team Lead
Contract B2B
Contract duration:

• 1 role – 3-month full-time contract
• 1 role – 6-month full-time contract

About the company and project:

The recruitment is for a global data and technology company that develops advanced analytics solutions to support data-driven marketing decisions for leading international brands. The focus of the project is on scaling a centralized data science platform used for Marketing Mix Modeling (MMM), Incrementality Testing, and Geo-Testing. Additionally, the role will contribute to the development of an offshore delivery capability in India to support global operations.

,[Define and execute the product roadmap for advanced analytics measurement solutions (MMM, Incrementality, Geo-Testing), Collaborate with data science, engineering, and business teams to build scalable and integrated analytics products, Lead the migration of locally developed MMM models to a centralized global platform, Design and implement geo-testing and incrementality measurement frameworks (e.g., A/B tests, causal inference models), Support product adoption through documentation, onboarding, and internal training, Define success metrics and monitor performance through automated reporting and dashboards] Requirements: Product development