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Компания: Intch
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A multi-platform subscription product conducts 10+ parallel A/B tests on weekly sprints. The company is hiring its first product analyst to ensure data-driven decision-making and validate product hypotheses. This is not a reporting or dashboarding role. You will challenge product decisions with data, surface insights proactively, and influence roadmap priorities based on empirical evidence. Key responsibilities include validating test outcomes for statistical significance, analyzing funnel behavior and cohort trends, and questioning hypotheses when data contradicts assumptions. You report directly to leadership and collaborate daily with Product, Marketing, Support and Engineering teams. Success is measured by decision quality and product impact, not by the volume of reports produced. What you'll do Challenge product decisions: pressure-test hypotheses before they go into a sprint, and question results that look too good to be true Look for insights across the funnel without waiting to be asked (activation, onboarding, paywall, conversion, post-purchase behavior) and turn them into concrete backlog proposals Dig into retention, churn (7d/30d+) and ARPU/ARPPU, segmenting by geo, platform, source, intent and behavior to find where growth actually comes from Own the full experiment cycle across 10+ parallel tests: hypothesis, metrics, guardrails, analysis, and a clear call to ship, stop, iterate or extend Make honest calls on small samples using a primary metric with guardrails, stopping rules, sanity checks and transparent assumptions, without false confidence Make sure the numbers can be trusted: validate tracking on critical paths (onboarding, paywall, purchase, renew/cancel/refund), measure broken events and get them fixed with engineering Build a shared language for metrics: a lean event taxonomy and glossary that Product and Marketing actually agree on Package findings into short, decision-ready memos, not black boxes What we're looking for Product analytics experience in subscription products, especially funnel, onboarding, paywall and conversion A proven track record of changing product decisions with data — you've said "the data doesn't support this" and made it stick Strong experiment design and A/B interpretation: metrics, segments, guardrails, distinguishing real effects from noise Cohort and behavioral analysis that translates into product actions, not just averages Hands-on expertise with Amplitude, Google Analytics and Google Sheets; able to build a complete picture from available data without a data warehouse or BI tool Clear communication of findings and uncertainty to non-analysts, with the ability to hold ground when it matters