About Tripadvisor
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork.
At Tripadvisor experiences, the only thing we love more than travel is data. We slice it, we dice it, and we use it to empower our decision making.
About The Role
As our Senior Product Data Scientist, you will be the cornerstone of our advanced analytics capability. This is more than a technical role; it’s a high-impact position designed to shape the future of our product by embedding deep, quantitative intelligence into its core. You will help set the vision for how data science can solve our most challenging problems. You will act as a catalyst, mentoring a talented team of product analysts while spearheading the development of models and frameworks that drive our product strategy forward.
What You Will Do
* Lead the development of Data Science within Product, producing statistical models that directly impact the insights and recommendations that drive the product and customer experience.
* Use your knowledge and experience to help scale the impact of the Product Analytics team through data science, creating automation, self service model capability, improving experimentation velocity, and driving efficiency.
* Architect and implement sophisticated statistical models (predictive, classification, clustering, etc.) to enhance product features like personalization and recommendations.
* Explore new tooling, product and approaches including Agentic AI and AI Agents, to identify opportunity areas, explore through POC to then drive adoption.
* Partner with Product Managers, Designers, and Engineers to identify high-impact opportunities where data science can solve customer problems and improve the product.
* Champion experimentation by designing and analyzing complex AB tests, causal inference models, and uplift modeling to inform product decisions.
* Guide and mentor other product analysts in best practices for experimentation, modeling, and data-driven product development upskilling the team and defining the roadmap for Product Data Science.
* Communicate complex data insights to both technical and non-technical stakeholders with clarity and influence.
Skills & Experience
* Significant experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization.
* Advanced proficiency in Python and SQL; deep, hands‑on experience with statistical modeling, experimentation, multi‑arm bandit, and a wide range of machine learning techniques (e.g., regression, classification, clustering).
* Demonstrated ability to define, implement, and operationalize crucial product and feature-level metrics from scratch.
* Proactive and collaborative approach with proven ability to lead technical discussions, drive product strategy, and communicate complex insights effectively to cross‑functional partners (e.g., Product, Engineering, Design teams).
* Experience scaling impact through creation of automated processes, self‑service tools, or data products.
* Demonstrated critical thinking: previous experience analyzing facts, evidence, observations, and arguments to form judgments via rational, skeptical, unbiased analysis.
* Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Nice To Haves
* Advanced programming background to build simulations and prototype data products.
* Experience validating quantitative findings with qualitative methods (e.g., surveys, user research).
* Demonstrated experience with applied AI, such as NLP, Large Language Models (LLMs), or Agentic AI for analytics.
* Deep experience developing sophisticated customer segmentation models including predictive LTV modeling.
* Experience working within a two‑sided marketplace, e‑commerce, or the travel technology industry.
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