Product & E‑Commerce Performance Analytics

About the role: We’re looking for a Data Analyst to join FactFinder and help drive product decisions with rigorous measurement and clear insights. This role is centered on investigations, product analytics, and experiment evaluation across key e‑commerce journeys—especially discovery and performance topics like search, ranking, and conversion. You’ll partner day-to-day with Product Managers, Engineers, and commercial stakeholders to define success metrics, validate impact of product changes, and uncover opportunities to improve customer experience and business outcomes. What you’ll do: Product analytics & decision support -Own measurement for FactFinder product initiatives: translate product questions into clear metrics, analysis plans, and recommendations -Build product performance narratives: what changed, why it changed, and what to do next Investigations & deep-dives -Lead deep-dive analyses into customer behavior, conversion drivers, and funnel drop-offs (browse → search → PDP → cart → checkout) -Diagnose KPI movements (e.g., conversion, revenue, engagement, add-to-cart rate) with structured root-cause analysis Search & ranking analytics (FactFinder focus) -Evaluate search and product ranking quality using both product and business metrics (e.g., CTR, zero-results rate, refinement rate, add-to-cart, downstream conversion, revenue per search) -Identify patterns in underperforming queries/categories and propose improvements (e.g., relevance tuning opportunities, merchandising gaps, data/instrumentation issues) Experimentation & uplift measurement -Partner with product and engineering to design measurable rollouts and experiments -Analyze A/B tests and quasi-experiments: define primary/guardrail metrics, validate data quality, interpret results, and communicate tradeoffs -Apply sound methods for incrementality/uplift and understand when results are biased (seasonality, novelty effects, selection bias) Data foundations -Create and maintain analysis-ready datasets (tables/views) and reusable metric definitions (single source of truth) -Write efficient, scalable SQL and collaborate with data engineering on pipelines, instrumentation, and data quality monitoring -Build dashboards/monitoring to track key FactFinder KPIs and proactively surface anomalies Stakeholder communication -Present findings clearly to both technical and non-technical audiences -Turn complex analyses into crisp product recommendations (ship / iterate / stop, and what to test next) What we’re looking for (Requirements)Must-have -Strong analytical problem-solving skills and a structured approach to investigations -Advanced SQL (joins, window functions, CTEs, performance-aware querying) with large datasets -Experience analyzing product and funnel metrics and explaining KPI changes in business terms -Practical understanding of experimentation (A/B tests, statistical significance, power/variance, guardrails, segmentation) -Strong communication: able to write and present clear, actionable insights -Experience in e-commerce / marketplace / digital product analytics (or comparable high-traffic product environment) Nice to have -BigQuery (or similar cloud warehouse) and data modeling best practices -Python for analysis (pandas, notebooks) and basic automation -Familiarity with event tracking/instrumentation (e.g., clickstream events, taxonomy, data quality checks) -Understanding of ranking/search systems and relevance measurement concepts -BI/dashboarding experience (Looker, Tableau, Power BI, or similar) How success looks in this role -FactFinder product teams trust your metrics and use your insights to make decisions -Investigations shorten “time-to-answer” when performance changes or issues occur -Experiments are measured reliably, with clear conclusions and follow-up actions -Core FactFinder KPIs are well-defined, monitored, and explainable