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About the Role
As a Senior Manager of Product Data Science, you will be a key leadership figure responsible for building and scaling a high-performing team of Analysts and Data Scientists. You will deliver impact through your team, raise the analytical and technical bar of the organization, and act as a force multiplier for decision-making quality.
Responsibilities
- 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
- Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization.
- 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).
- Demonstrated ability to define, implement, and operationalise crucial product and feature-level metrics from scratch.
- 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).
- Experience scaling analytics or data science capabilities, driving impact through the creation of automated processes, self-service tools, or data products.
- 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.
- Outstanding leadership skills, with experience in mentoring, coaching, and developing teams of analysts or data scientists.
- Exceptional collaboration and communication skills, with the ability to engage, influence, and inspire cross-functional partners at all levels.
- 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.
- 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.
Skills
- Python
- SQL
- Statistical modeling
- Experimentation
- Machine learning techniques (e.g., Regression, Classification, Clustering)
- Product metrics definition and implementation
- Strategic influence
- Critical thinking
- Leadership
- Mentoring
- Coaching
- Team development
- Collaboration
- Communication
- Cross-functional partnership
- AI
- Large Language Models (LLMs)
- Agentic AI
- Automation technologies
Location
- Hybrid
Work Type
- Hybrid
- Full-time
Experience Level
- Senior
- Manager
Education Level
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
About the Company
- Tripadvisor is the world’s largest online travel site, visited by 390 million travellers each month.
- The Experiences business, Viator, is a fast-evolving and highly data-driven part of the organisation.
- At Viator, data is at the heart of how they build great products, used to understand customers, improve decision-making, and drive measurable business impact.