Senior Manager, Product Data Science & Analytics

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.

• 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.

Skills & Experience

• 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.

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences, so we can collectively revolutionize travel and together find the good out there.

Tripadvisor is the world's largest online travel site, visited by 390 million travellers each month, and our Experiences business, Viator, is a fast-evolving and highly data-driven part of the organisation.

At Viator, data is at the heart of how we build great products. We use it to understand our customers, improve decision-making, and drive measurable business impact.

• 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.