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Senior Manager, Product Data Science & Analytics

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Published
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3Application actions
24 Sep 2026Apply before
Opportunity details

About this role.

AI Summary

Tripadvisor is seeking a senior people and technical leader to scale Product Data Science and Analytics for its Viator Experiences business. The role leads analysts and data scientists embedded in product domains while setting standards for experimentation, causal inference, modeling, and product measurement. It partners closely with Product, Engineering, Design, Marketing, Commercial, Data Platform, and Data Engineering leaders to turn ambiguous opportunities into measurable decisions and roadmaps. The successful candidate will combine expert Python and SQL capabilities with strategic influence, organizational change leadership, and a record of developing high-performing technical teams.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior leadership position requiring both deep hands-on credibility in product data science and the ability to improve analytical maturity across multiple teams. The role operates in ambiguous, high-scale product environments and requires influencing senior stakeholders without direct authority.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$190,000
US market range$165k–$230k
AI insightNo compensation is disclosed, so these figures are estimated for the US market in USD. For a Senior Manager leading Product Data Science and Analytics at a large technology or marketplace company, an estimated annual base-salary median is $190,000, with a typical market range of $165,000 to $230,000; bonus, equity, and location differentials may materially change total compensation.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you raise experimentation quality across several product teams with different levels of analytical maturity?

I would first assess current practices, instrumentation, decision workflows, and common failure modes. I would then establish pragmatic standards for hypotheses, metrics, power, guardrails, and readouts; provide reusable tooling and templates; and create a review process for high-impact tests. Success would be measured through adoption, faster trustworthy decisions, and improvements in experiment quality rather than process compliance alone.

Describe how you would translate an ambiguous product problem into a data-science roadmap.

I would clarify the business objective, user behavior to influence, constraints, and decision owner before defining a measurable outcome. Next, I would decompose the problem into instrumentation, descriptive analysis, segmentation, causal measurement, and predictive or optimization opportunities. I would prioritize work by expected impact, confidence, effort, and dependency risk, then communicate a phased roadmap with clear decision points.

What metrics would you use to evaluate a new marketplace product feature?

I would define a north-star outcome tied to customer and marketplace value, such as qualified booking conversion or successful experience completion. I would pair it with leading indicators, segment-specific metrics, and guardrails including cancellation, customer support contacts, supplier impact, and long-term retention. I would ensure the metrics are instrumented consistently and use an experiment or credible quasi-experimental design to estimate incremental impact.

How do you balance hands-on technical leadership with people management at this seniority?

I stay technically engaged by reviewing important analytical designs, challenging assumptions, and contributing to standards and architectural choices rather than becoming a bottleneck for every analysis. I delegate ownership with clear outcomes, coach managers and senior individual contributors, and reserve direct involvement for high-leverage or high-risk decisions. This keeps the team autonomous while preserving technical rigor and strategic alignment.

Tell us how you would influence a senior stakeholder who wants to launch based on inconclusive data.

I would acknowledge the urgency, make the uncertainty explicit, and explain what the evidence can and cannot support in business terms. I would offer practical options, such as a limited rollout with predefined guardrails, an additional targeted test, or a reversible launch, along with the risks of each choice. The goal is to enable an informed decision while protecting customers, product quality, and the organization’s trust in data.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

About Tripadvisor

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.

About the role:

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.

What You’ll Do

  • 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.

You could be an especially great fit if you 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.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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