Roles & Responsibilities

Own product insights across key journeys: onboarding → pairing → activation → daily engagement → retention → subscription → app store rating.
Build and maintain dashboards for core metrics (DAU/MAU, cohorts, retention, funnel conversion, feature adoption, paid conversion, churn).
Cohort + segmentation analysis: identify “who churns, when, and why” (device type, acquisition channel, behavior patterns, crash/sync issues, notification opt-in, etc.).
Detect problems early: build simple monitoring for spikes in churn signals (drop in sessions, sync failures, crash rate, support tickets).
Translate insights into actions: recommend specific product levers (UX fixes, nudges, education, feature tweaks), and define how success will be measured.
Experimentation support: design and evaluate A/B tests (or controlled rollouts), define success metrics + guardrails.
Triangulate with qual: combine data with app reviews, ratings, and support tickets to create a “top issues + impact” view.

The Ideal “Noisemaker”:

1–2 years experience in Product / Growth / Data Analytics (consumer apps preferred)
Strong SQL skills (joins, window functions, cohorts, funnels)
Proficient in Excel / Google Sheets (pivots, charts, basic modeling)
Strong understanding of product metrics (retention, funnels, cohorts, LTV basics)
Experience with BI & visualization tools: Tableau / Power BI / Looker
Hands-on experience in creating dashboards and KPI reporting
Good to have: Python for analysis and automation
Familiarity with Figma and collaboration with design teams
Ability to tell a story with data: insights → recommendation → impact
Comfortable working cross-functionally with PMs, designers, engineers
Experience with analytics/event tools: Amplitude / Mixpanel / Firebase / GA4

Product Analyst