7 дней назад
Data Scientist, Experimentation
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist, Experimentation (Python/SQL): Designing and analysing end-to-end experiments for Viator product teams with an accent on statistical power, metric design, data quality, and causal inference. Focus on building reusable experimentation tooling, diagnosing invalid or surprising results, and translating statistical findings into product recommendations.
Location: London, United Kingdom; hybrid work
Company
is a travel experiences marketplace within Tripadvisor, connecting travellers with experiences through technology, content, and marketplace products.
What you will do
- Design and analyse experiments end to end with Product Managers and Engineers.
- Translate product questions into testable hypotheses, primary metrics, and appropriate guardrails.
- Define and instrument feature-level metrics while assessing sensitivity and interpretation.
- Check assignment integrity, exposure, and data quality before drawing conclusions from results.
- Build reusable queries, tooling, templates, documentation, and shared experimentation protocols.
- Communicate positive, negative, and inconclusive findings with clear recommendations.
Requirements
- Solid experience in data science or a similar quantitative role supporting product teams.
- Strong understanding of experimentation, statistical power, minimum detectable effect, metric selection, and experiment validity.
- Strong proficiency in Python and SQL, with hands-on experience in statistical analysis and experimentation.
- Exposure to statistical modelling or machine learning techniques such as regression and classification.
- Experience defining and operationalising product and feature-level metrics and partnering with Product Managers and Engineers.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
Nice to have
- Experience with sparse conversion, heavy-tailed revenue, or slow-to-observe outcomes.
- Familiarity with variance reduction and causal inference methods.
- Experience with Statsig, Eppo, GrowthBook, or an in-house experimentation platform.
- Experience in a high-scale consumer marketplace, e-commerce, or travel product.
- Interest in using modern AI tooling to improve analysis and experimentation.
Culture & Benefits
- Mentorship and review from senior and principal data scientists.
- Collaboration with product and engineering teams across .
- Focus on clear documentation, consistent practices, and inclusive candidate experiences.
- Reasonable accommodations are available during the application and recruiting process.
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