Data Scientist/Engineer – Online Metrics

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search, and specialized datasets, combined with both frontier and in-house models, create the best possible experience for our users. As a Data Scientist/Engineer on this team, you will derive online signals from user interactions to bridge the gap between changes in answer quality and observed user behavior.ResponsibilitiesDiscover and validate online signals from user interactions that serve as reliable proxies for true answer qualityDesign and implement novel online metrics to be tracked both in A/B testing and on product health dashboards, ensuring alignment with ground-truth evaluationsAnalyze experimental results to validate these metrics, ensuring they accurately predict user satisfaction and drive product decisionsBuild and maintain the data pipelines that calculate these metrics at scale, delivering actionable quality signals to Search, Product, and model training teamsCommunicate findings and bring clarity through close collaboration with Product and Search teamsOperate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer QualityQualificationsMS in a technical field or equivalent experience4+ years of experience working as a Data Scientist, Analytics Engineer, or related roleExperience working on search, recommendation, or LLM-based products, with an emphasis on designing online metrics and analyzing A/B experimentsStrong proficiency in Python and SQL (expected to write production-grade code)Deep knowledge of statistical analysisExperience with Business Intelligence (BI) tools for visualization and reportingComfortable with agentic coding workflows and using AI-assisted development tools to iterate fasterPreferred QualificationsProficiency with Apache Spark and DatabricksExperience with the development or validation of LLM-as-a-judge systemsPrior work supporting customer-facing products at scale