Senior Product Manager
Senior Product Manager
📍 Location: London, London, United Kingdom
🏢 Industry: Software development
💼 Work Setting: Hybrid
Are you a data-driven Product Manager passionate about machine learning, recommendation engines, personalization, and customer experience optimization?
We are seeking a Senior Product Manager to lead the vision, strategy, and execution of recommendation and ranking products that power customer experiences across the platform. This role sits at the intersection of Product, Data Science, Engineering, Analytics, Growth, and Commercial teams, driving algorithms that connect customers with the most relevant partners, restaurants, and products.
The ideal candidate combines expertise in product management, machine learning products, experimentation, personalization, recommendation systems, customer analytics, and stakeholder management with a strong passion for solving customer problems through data-driven innovation.
Key Responsibilities
Product Strategy & Vision
- Define and own the product vision, strategy, and roadmap for recommendation and ranking systems.
- Align product priorities with customer, business, commercial, and operational objectives.
- Develop strategic plans that improve customer engagement and business performance.
- Drive long-term innovation within personalization and recommendation platforms.
- Identify opportunities to create competitive advantage through intelligent product experiences.
Recommendation & Ranking Products
Lead products focused on:
- Homepage Ranking
- Restaurant Recommendations
- Personalized Discovery Experiences
- Partner Recommendations
- Customer Personalization
- Sponsored Placement Optimization
- Revenue Optimization Algorithms
Ensure recommendation systems deliver highly relevant and engaging customer experiences.
Machine Learning Product Management
- Collaborate closely with:
- Data Scientists
- Machine Learning Engineers
- Software Engineers
- Analytics Teams
- Define business requirements for ML-driven solutions.
- Translate customer and business needs into algorithmic products.
- Prioritize model improvements and experimentation opportunities.
- Bridge technical and non-technical stakeholders.
Customer Behavior Analysis
- Develop a deep understanding of customer behavior and decision-making patterns.
- Analyze customer journeys and engagement metrics.
- Identify opportunities to improve customer discovery and conversion.
- Use quantitative and qualitative insights to guide product decisions.
- Support customer-centric product innovation.
Data Analysis & Insights
- Leverage data to identify trends, opportunities, and performance gaps.
- Analyze large datasets to understand recommendation effectiveness.
- Monitor business impact of ranking and recommendation changes.
- Drive data-informed decision-making across product initiatives.
- Evaluate product success through clear performance measurement.
Experimentation & A/B Testing
- Design and execute A/B tests to validate product hypotheses.
- Develop experimentation frameworks for recommendation and ranking systems.
- Measure customer, operational, and commercial outcomes.
- Use experimentation results to refine product strategies.
- Promote a culture of evidence-based product development.
KPI Ownership & Performance Management
Define and monitor key performance metrics, including:
Customer Metrics
- Engagement
- Conversion Rates
- Retention
- Customer Satisfaction
Marketplace Metrics
- Partner Visibility
- Customer Matching Quality
- Order Growth
Commercial Metrics
- Revenue Growth
- Sponsored Product Performance
- Advertising Revenue
Operational Metrics
- Recommendation Quality
- Algorithm Performance
- Marketplace Efficiency
Product Discovery
- Lead discovery activities to uncover customer and business needs.
- Conduct:
- User Research
- Data Analysis
- Competitive Analysis
- Market Assessments
- Validate opportunities before development begins.
- Prioritize initiatives based on business value and customer impact.
Backlog & Delivery Management
- Own and prioritize the product backlog.
- Balance customer needs, technical constraints, and business priorities.
- Work within Agile product development environments.
- Ensure timely and effective feature delivery.
- Drive alignment across cross-functional teams.
Stakeholder Communication
- Communicate product vision, priorities, and outcomes to stakeholders.
- Present recommendations and product strategies to leadership.
- Build alignment across:
- Engineering
- Data Science
- Growth Teams
- Commercial Teams
- Executive Leadership
- Ensure transparency throughout the product lifecycle.
Qualifications
Experience
Required
- Proven Product Management experience managing data-driven products.
- Experience building and managing:
- Recommendation Systems
- Personalization Products
- Search Products
- Ranking Algorithms
- Machine Learning-Based Solutions
- Experience working with engineering and data science teams.
- Experience delivering products in Agile environments.
Technical & Analytical Skills
Product Management
- Product Strategy
- Roadmap Development
- Product Discovery
- Backlog Management
- Stakeholder Management
Machine Learning & Data Science
- Recommendation Systems
- Ranking Algorithms
- Personalization
- Machine Learning Concepts
- Data-Driven Product Development
Analytics
- KPI Development
- Customer Analytics
- Behavioral Analysis
- Experiment Design
- Performance Measurement
Experimentation
- A/B Testing
- Hypothesis Testing
- Product Optimization
- Statistical Thinking
Professional Skills
- Strategic Thinking
- Customer Obsession
- Analytical Problem Solving
- Communication & Influence
- Cross-Functional Leadership
- Decision Making
- Collaboration
- Innovation Mindset
Core Competencies
- Product Management
- Recommendation Systems
- Ranking Algorithms
- Personalization
- Machine Learning Products
- Data Science Collaboration
- Customer Analytics
- A/B Testing
- Product Strategy
- User Behavior Analysis
- Growth Optimization
- Marketplace Optimization
- Revenue Optimization
- Agile Product Development
- Stakeholder Management