Principal Data Scientist, Experimentation
About this role
Tripadvisor needs a Principal Data Scientist to solve the challenge of unreliable measurement and slow decision-making across complex travel marketplaces like Viator. Without robust experimentation frameworks, teams struggle to evaluate changes on low-traffic surfaces or where long-horizon outcomes take months to appear. This individual contributor will build the technical capabilities that allow teams to test effectively without central bottlenecks, defining standards from traditional A/B testing to causal inference and Bayesian methods.
Working closely with Product, Engineering, and Data Platform groups, the person in this role will design custom measurement strategies for complex questions and serve as the final technical authority on validity. Success requires deep statistical expertise paired with the ability to scale good practices through tooling, automation, and mentorship. The ideal candidate has extensive quantitative experience in high-scale environments, combining rigorous methodological design with strong cross-functional influence.
What you will do
- Establish the technical standard for experimentation across Product Data Science, implementing protocols for A/B testing, quasi-experimental designs, and Bayesian methods.
- Collaborate with Product, Engineering, and Data Platform teams to increase experimentation velocity while maintaining analytical rigor.
- Address complex measurement challenges for Viator, designing custom methodologies where standard experimentation falls short.
- Act as the primary technical authority on measurement validity by reviewing disputed results and determining evidential support.
- Standardize recurring analytical processes using automation and AI capabilities to improve throughput and quality.
- Develop organisation-wide improvements such as variance reduction for difficult metrics and proxy metrics for long-horizon outcomes.
- Mentor senior data scientists and review experimental designs to raise the technical capability of the wider team.
What you need
- Extensive experience in data science or a related quantitative role with a track record of supporting product organisations.
- Authoritative command of experimentation methods, including experimental design, causal inference, multi-arm bandits, and Bayesian approaches.
- Expert-level proficiency in Python and SQL.
- Hands-on background in statistical modelling, regression, classification, clustering, and quasi-experimentation.
- Demonstrated ability to define and operationalise product and feature-level metrics from scratch.
- Experience standardizing frameworks across multiple teams to increase experimentation speed and quality.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Nice to have
- Experience with experimentation in a two-sided marketplace involving interference between users and shared supply.
- Background in building and validating proxy or surrogate metrics for long-horizon outcomes.
- Experience with Bayesian and hierarchical approaches for low-traffic surfaces.
- Familiarity with building or improving experimentation platforms and self-service data products.
- Experience with SaaS experimentation tools such as Statsig, Eppo, or GrowthBook.
Skills and tech stack
Questions candidates ask
What is the work model for this position?
The posting indicates a hybrid work arrangement based on the location tag.
What technical stack will I use?
The role requires expert-level proficiency in Python and SQL, alongside familiarity with experimentation tools such as Statsig, Eppo, or GrowthBook.
Who will I collaborate with?
You will partner closely with Product, Engineering, and Data Platform teams to improve experimentation velocity and design measurement approaches.
What is the primary focus of the role?
The position serves as a leading individual contributor responsible for setting experimentation standards, tooling, and protocols across the organisation.