Senior Data Scientist - Search

Role overview A senior data scientist position focused on search quality, combining deep analytics with hands-on model building. The role partners closely with engineering, product, design, and ML teams to shape query understanding, retrieval, and ranking across a large-scale consumer platform that connects people, places, posts, and local businesses. It is a hybrid analyst-plus-builder opportunity, owning problems end-to-end from framing the question to shipping improvements in production.

Responsibilities - Design and build algorithms that improve search relevance, retrieval quality, and ranking for both user-facing discovery and business-discovery use cases. - Plan, run, and analyze A/B experiments, including early-stage feature monitoring and post-launch follow-ups to confirm durable impact. - Translate ambiguous product questions into data analyses that surface strategic insights, and evaluate the effect of ranking and content changes. - Develop scalable metrics, dashboards, and evaluation frameworks that track performance across query understanding, retrieval, ranking, and downstream engagement. - Partner with product, design, engineering, marketing, and operations to embed data-informed decision making throughout development. - Champion data quality and help colleagues across the company use data effectively.

Requirements - 5+ years of relevant data science experience, ideally on a search, recommendation, or information retrieval product. - Hands-on familiarity with query understanding, retrieval, ranking, and the metrics used to evaluate them. - Working knowledge of machine learning models, plus the judgment to choose the right approach and define meaningful evaluation metrics. - Strong experience designing and analyzing complex product experiments, including interaction effects and long-term metric movement. - Expert SQL and Python skills, including scientific computing tools such as numpy, pandas, and scikit-learn. - Excellent communication skills, with the ability to simplify complex findings and tell a clear story to varied audiences including executives.

Nice to have - Experience with ranking algorithms for unstructured content. - Experience deploying or monitoring ML models in production. - Familiarity with building retrieval-augmented generation systems.

Benefits and work setup - Hybrid work model combining in-office and remote time, with offices in several major US cities and London. - Salary range noted in the source material as approximately $175,000–$234,000 annualized, depending on skills, experience, proficiency level, and geographic location, plus a meaningful equity grant with quarterly vesting.