About this role
Tripadvisor needs a Data Scientist to address the challenge of measuring product changes accurately in a marketplace where bookings occur infrequently and supply remains finite and shared. Operating within the Viator experimentation team, this individual will collaborate closely with product managers and engineers to determine whether shipped updates achieve their intended goals. The work involves designing end-to-end experiments, establishing robust primary and guardrail metrics, and scaling testing efficiency through reusable tooling, clear documentation, and consistent protocols. Beyond standard A/B testing, the team dives deep into behavioural analysis, opportunity sizing, and observational measurement where randomisation proves difficult.
Candidates joining the group will navigate complex analytical problems under the guidance of senior and principal practitioners who offer mentorship and review. Success in the position requires a strong foundation in statistics, deep technical proficiency in Python and SQL, and a critical mindset that verifies data integrity before drawing conclusions. A qualified professional will enjoy translating ambiguous product questions into testable hypotheses while communicating both positive and negative findings clearly across technical and non-technical stakeholders.
What you will do
- Design and analyse end-to-end experiments alongside product managers and engineers.
- Translate product questions into testable hypotheses with pre-registered metrics and guardrails.
- Define and instrument feature-level metrics while evaluating their sensitivity and interpretation.
- Verify data quality, assignment integrity, and exposure before drawing conclusions from test results.
- Build reusable queries, tooling, and templates to streamline the experimentation workflow for product teams.
- Communicate findings clearly to diverse audiences with actionable recommendations attached.
- Conduct supplementary analyses such as opportunity sizing, behavioural tracking, and observational measurement.
- Document hypotheses, designs, and outcomes to preserve organizational learning over time.
What you need
- Solid professional background in data science or a comparable quantitative discipline supporting product teams.
- Sound understanding of statistical experimentation principles, including statistical power and common validity threats.
- Strong technical proficiency in Python and SQL for statistical analysis and experimentation.
- Familiarity with statistical modelling or machine learning techniques such as regression and classification.
- Demonstrated ability to define and operationalise feature-level metrics in collaboration with colleagues.
- Experience partnering directly with engineering and product management stakeholders.
- Clear written and verbal communication skills for explaining statistical concepts to non-technical audiences.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Nice to have
- Experience with metrics that are difficult to measure such as sparse conversion or heavy-tailed revenue
- Familiarity with variance reduction techniques for sensitivity
- Exposure to causal inference methods for non-randomised situations
- Experience with SaaS experimentation tools like Statsig, Eppo, GrowthBook, or in-house platforms
- Experience in high-scale consumer product environments such as marketplaces or travel platforms
Skills and tech stack
Questions candidates ask
What is the work environment policy for this role?
The posting indicates a hybrid work model with the identifier LI-Hybrid. The position is based in London.
What core technical skills are required for the position?
Candidates must have strong proficiency in Python and SQL, along with hands-on experience in statistical analysis and experimentation. Some exposure to machine learning techniques like regression and classification is also expected.
How does the team support professional growth?
Team members grow their depth in experimentation and causal inference through review and mentorship from senior and principal data scientists. You will be supported by experienced practitioners who navigate complex marketplace problems.
Who can candidates contact for hiring accommodations?
Candidates who need a reasonable accommodation during the application or recruiting process can reach out to their individual recruiter or contact the team at AccessibleRecruiting@tripadvisor.com.