Product-oriented Analyst analyzing metrics and client behavior to drive business outcomes for clients. Working with multiple data sources and collaborating with stakeholders in a hybrid work environment.
Responsibilities
Increase the speed and quality of product hypothesis validation.
Analyze core product funnels and metrics: registration → KYC → first deposit, repeat deposits, retention, churn, LTV, ARPU/ARPPU, client engagement, etc.
Work with data from multiple sources: Google Analytics 4, ClickHouse, BigQuery (or other DWH), payment providers, CRM, marketing platforms, and internal event tracking.
Design, monitor, and analyze A/B tests and product experiments (features, UX flows, promos, bonus mechanics) and translate results into actionable product decisions.
Build and maintain dashboards in BI tools (Looker Studio, Tableau, etc.) for product and business stakeholders.
Perform cohort, segmentation, and retention analysis across markets, devices, and client segments (new vs returning, VIP, high-risk, etc.).
Conduct deep-dive investigations into metric drops, anomalies, and performance issues; identify growth drivers and potential risks.
Translate business questions into structured analytical tasks: define hypotheses, success metrics, and analytical approaches together with product managers.
Contribute to tracking and data quality: define product event requirements and collaborate with developers and analytics engineers to ensure data completeness and accuracy.
Prepare clear presentations and visualizations to communicate insights to both technical and non-technical stakeholders (Product, Marketing, Risk, Leadership).
Requirements
3+ years of experience in product or data analytics.
Strong SQL skills: complex joins, window functions, CTEs, and query optimization for large datasets (ideally ClickHouse and BigQuery).
Hands-on experience working with GA4 data (events, parameters, user properties, funnels, explorations; exporting GA4 data to DWH is a plus).
Practical experience with at least one modern BI tool (Looker Studio, Tableau, etc.) — building interactive dashboards for stakeholders.
Experience planning and analyzing A/B tests: metric selection, statistical significance validation, and clear interpretation of results.
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