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# Principal Product Data Scientist

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/tripadvisor.md)Share25 Aug 2026Published39Listing views3Application actions24 Sep 2026Apply before  Opportunity details

## About this role.

AI SummaryTripadvisor is seeking a Principal Product Data Scientist to serve as the senior technical leader for Product Data Science. The role sets data-science strategy, leads complex product analytics, and embeds experimentation, causal inference, predictive modeling, and AI into product decisions. It requires expert Python and SQL skills alongside the ability to influence senior Product, Engineering, Design, and commercial stakeholders. The successful candidate will scale analytics through automation and self-service capabilities while mentoring data scientists and analysts. Experience in marketplaces, e-commerce, travel technology, applied AI, and qualitative research validation is especially relevant.

## Role DNA

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

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a principal-level role combining hands-on statistical and machine-learning depth with organization-wide technical leadership. The candidate must independently resolve ambiguous, high-impact product questions and influence senior cross-functional leaders.

## Salary analysis

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

Estimated job medianMarket rate$205,000US market range$170k–$250k0$275k

AI insightNo actual salary or compensation range is disclosed in the posting. These figures are estimated annual USD base-salary market benchmarks for a Principal Product Data Scientist in the US market, reflecting the role's seniority, advanced experimentation and ML requirements, and strategic leadership scope; actual compensation in Poland may differ materially.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Product data science](https://jobicy.com/jobs?search_keywords=Product%20data%20science.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Statistical modeling](https://jobicy.com/jobs?search_keywords=Statistical%20modeling.md)[Experimentation](https://jobicy.com/jobs?search_keywords=Experimentation.md)[Causal inference](https://jobicy.com/jobs?search_keywords=Causal%20inference.md)[Machine learning](https://jobicy.com/jobs?search_keywords=Machine%20learning.md)[Uplift modeling](https://jobicy.com/jobs?search_keywords=Uplift%20modeling.md)[Customer segmentation](https://jobicy.com/jobs?search_keywords=Customer%20segmentation.md)[AI and LLMs](https://jobicy.com/jobs?search_keywords=AI%20and%20LLMs.md)

Sample interview questionsHow would you establish a data science strategy for a product organization with multiple competing priorities?I would start by aligning on company objectives and product bets, then map the highest-value decisions to measurable metrics and analytical capabilities. I would assess existing data quality, experimentation maturity, tooling, and team capacity, prioritize initiatives by expected impact and feasibility, and publish a roadmap with clear ownership and success criteria. Regular stakeholder reviews would keep the strategy responsive while preserving technical rigor.

Describe how you would evaluate the causal impact of a new product feature when a randomized experiment is not feasible.

I would first define the treatment, eligible population, outcome metrics, and likely confounders. Depending on the rollout and data structure, I would consider methods such as difference-in-differences, matching or weighting, regression discontinuity, interrupted time series, or synthetic controls. I would test assumptions, run placebo and sensitivity analyses, quantify uncertainty, and communicate both the estimated impact and limitations clearly.

How would you use multi-armed bandits instead of conventional A/B testing for product optimization?

I would use a multi-armed bandit when the product can safely adapt allocation over time and the goal is to reduce opportunity cost while learning which variant performs best. I would define a reliable reward metric, choose an exploration strategy such as Thompson sampling, implement guardrails for key customer and business metrics, and monitor for delayed outcomes, segment bias, and nonstationarity. For decisions requiring a stable causal estimate, I would retain or supplement with randomized experimentation.

Give an example of how you would turn an ambiguous leadership question into an actionable data-science project.

I would clarify the business decision, the affected users, desired outcome, and time horizon before translating the question into hypotheses and measurable metrics. I would audit available data, identify knowledge gaps and risks, and propose an analysis or experiment with explicit decision thresholds. I would then present the result as a recommendation, including expected impact, uncertainty, trade-offs, and next actions rather than only technical findings.

How would you scale data-science impact beyond a small team of specialists?

I would identify recurring analyses and convert them into trusted datasets, metric definitions, automated pipelines, experimentation templates, and self-service tools. I would establish documentation, governance, quality checks, and training so Product and Engineering partners can answer routine questions safely. The data science team could then focus on complex causal, predictive, and strategic problems while mentoring others on sound analytical practices.

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 a Principal Product Data Scientist, you will operate as the most senior technical leader in the Product Data Science function. You will shape the vision, set the technical direction, and drive strategic impact through innovative analytical solutions. This role is both highly technical and deeply collaborative, requiring excellence in leadership, communication, and cross-functional influence.

What You will do:

* Lead and define the Data Science strategy for Product, ensuring that advanced analytics, data science, and AI methodologies are central to how we build great products and improve customer experiences.
* Serve as a trusted strategic advisor to senior Product and Engineering leadership, ensuring that data-driven decision making is embedded at the highest levels of the organization.
* Drive the development and adoption of next-generation data science tooling, platforms, and frameworks, with a focus on automation, scalability, and reproducibility.
* Spearhead the exploration and integration of emerging AI technologies, such as Agentic AI and AI Agents, identifying and developing high-impact use cases from POC to production.
* Champion best practices in experimentation, causal inference, and uplift modeling, ensuring statistical rigor in decision-making processes.
* Take ownership of the most complex, high-profile analytical projects, translating ambiguous questions into clear, actionable recommendations that deliver commercial and customer value.
* Mentor, coach, and develop other Data Scientists and Analysts, fostering a culture of critical thinking, continuous learning, and technical excellence.
* Lead initiatives to scale impact through automation, self-service, and democratization of data science capabilities.
* Develop sophisticated customer segmentation, and predictive models that directly inform and optimize the product roadmap.
* Communicate complex analytical and technical concepts to diverse audiences, influencing stakeholders across Product, Engineering, Design, and Commercial teams.

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 operationalize 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 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.
* 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:

* Advanced programming background with the ability 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.

* Experience working within a two-sided marketplace, e-commerce, or the travel technology industry.
* Masters degree or equivalent relevant programs

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at AccessibleRecruiting@tripadvisor.com.

If you have any additional questions about careers at Tripadvisor you can email us at recruitment@tripadvisor.com. We have all the answers!

#LI-Remote

#LI-SM1

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[Apply now >](https://jobicy.com/jobs/151535-principal-product-data-scientist.md)

>  Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md)

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