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As a Senior Manager of Product Data Science, you will be a key leadership figure within the Product Data Science organisation, responsible for building and scaling a high-performing team of Analysts and Data Scientists embedded within Product domains. You will not only deliver impact through your team, but also raise the overall analytical and technical bar of the organisation, ensuring data science, experimentation, and product analytics are consistently applied at a high standard across multiple product areas. You will act as a force multiplier for decision-making quality, improving how Product, Engineering, Design, and Commercial teams use data to shape strategy, prioritise work, and evaluate impact.
Job Responsibility
Lead, develop, and grow a team of Product Analysts and/or Data Scientists, ensuring consistently high performance, strong technical standards, and clear ownership of impact
Drive effective goal-setting, planning and execution processes across Product Data Science, bringing leadership and discipline to OKRs, prioritisation and delivery against strategic objectives
Set and continuously raise the bar for analytical quality, experimentation rigour, and data science application across your teams, ensuring outputs are robust, actionable, and decision-oriented
Act as a senior technical and strategic leader, reviewing and shaping high-impact analytical work, experimentation design, and advanced modelling approaches where required
Partner closely with senior Product, Engineering, Marketing, and Commercial leaders to define priorities, shape roadmaps, and ensure data science is embedded in strategic decision-making
Translate ambiguous business problems into structured analytical and data science problems, ensuring your team delivers clear, commercially meaningful recommendations
Drive adoption of scalable analytical frameworks, experimentation standards, and AI-enabled tooling to improve efficiency, consistency, and speed of decision-making across teams
Champion best practices in experimentation, causal inference, segmentation, and customer understanding, ensuring statistical and analytical rigor across the organisation
Build and maintain strong partnerships with Data Platform, Data Engineering and other central data functions, ensuring the team can effectively leverage shared capabilities while influencing the long-term data ecosystem
Build and evolve the team's capability through hiring, coaching, and performance management, ensuring strong technical depth and leadership within the function
Identify and remove systemic blockers to high-quality analytics delivery, improving tooling, processes, ways of working and organisational effectiveness across Product Data Science while leading change that enables the team to scale
Influence and align cross-functional stakeholders across multiple product domains, ensuring clarity, prioritisation, and strong decision-making discipline
Requirements
Experience: Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization
Technical & Modeling Expertise: Expert Level proficiency in Python and SQL. Deep, hands-on experience with statistical modeling, (quasi) experimentation, multi-arm bandit, and a wide range of machine learning techniques (e.g., Regression, Classification, Clustering)
Product Acumen: Demonstrated ability to define, implement, and operationalise crucial product and feature-level metrics from scratch
Strategic Influence: A proven track record of driving strategic impact through proactive and collaborative approach with the proven ability to lead technical discussions, drive product strategy, and communicate complex insights effectively to cross-functional partners (e.g., Product, Engineering, Design)
Scaling Impact: Experience scaling analytics or data science capabilities, driving impact through the creation of automated processes, self-service tools, or data products
Critical Thinking: Leader in critical thinking, your previous experience will demonstrate the analysis of available facts, evidence, observations, and arguments in order to form a judgment by the application of rational, skeptical, and unbiased analyses and evaluation
Leadership: Outstanding leadership skills, with experience in mentoring, coaching, and developing teams of analysts or data scientists
Collaboration & Communication: Exceptional collaboration and communication skills, with the ability to engage, influence, and inspire cross-functional partners at all levels
Cross-Functional Partnership: Proven ability to build strong relationships and drive outcomes across Product, Engineering, Data Platform and other central functions, often without direct authority
Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field
Nice to have
Experience working within a high-scale technology company, marketplace, e-commerce business, or travel technology organisation
A strong technical background in Product Data Science, Data Science, Experimentation, or Machine Learning before moving into leadership roles
Experience building and scaling experimentation platforms, measurement frameworks, self-service capabilities, or data products
Experience applying AI, Large Language Models (LLMs), Agentic AI, or automation technologies to improve analytics productivity and decision-making effectiveness
Experience leading organisational change, improving analytical maturity, and raising standards across multiple teams or functions
A reputation for raising the standard of thinking, execution, and decision-making in every team and organisation you join