Data Analyst (Product Analytics)

As a Data Analyst, you will bridge the gap between complex numbers and strategic product execution. You will work closely with Product Managers, Engineers, and Marketing teams to track how users interact with our platform, optimize product features, measure KPI performance, and identify new opportunities for user retention and growth. The ideal candidate loves diving into large datasets, building automated dashboards, and telling a compelling story with data., * Product Insights & Tracking: Define, implement, and analyze core product metrics (e.g., Daily/Monthly Active Users, Feature Adoption Rates, Churn, User Lifetime Value, and Funnel Conversion rates).

• Data Visualization & Reporting: Design, build, and maintain automated, interactive business intelligence dashboards (using Tableau, Power BI, or Looker) to provide real-time visibility into product performance for stakeholders.
• A/B Testing & Optimization: Formulate hypotheses, design, and analyze A/B experiments to evaluate the impact of new features, UI/UX overhauls, and user onboarding flows.
• User Behavior Analytics: Deep dive into product usage data to uncover trends, identify bottlenecks in user journeys, and discover what drives long-term customer retention.
• Cross-functional Collaboration: Partner with Product Engineering to ensure proper telemetry and event-tracking (e.g., using Mixpanel, Amplitude, or Segment) are accurately integrated.
• Data Quality Assurance: Partner with Data Engineers to maintain data integrity, establish clear documentation/data dictionaries, and ensure data pipelines are processing cleanly.

Do you have experience in Statistical significance testing?, * Experience: 2-4+ years of experience as a Data Analyst, Product Analyst, or Business Intelligence Analyst, ideally working on a digital product/SaaS platform.

• SQL Proficiency: Advanced SQL skills are a must (ability to write complex joins, window functions, and optimize queries across large datasets).
• BI & Data Visualization: Strong experience creating production-grade dashboards in modern BI tools (Power BI, Tableau, Looker, or Sigma).
• Product Analytics Tools: Direct hands-on experience with product tracking instrumentation tools such as Amplitude, Mixpanel, Google Analytics 4 (GA4), Heap, or Segment.
• Programming Languages: Proficiency with Python or R for data manipulation, statistical analysis, and scripting is highly preferred.
• Statistical Foundatons: Solid understanding of statistics, particularly surrounding hypothesis testing, sample sizing, and regression models for A/B testing.
• Communication: Ability to translate complex analytical findings into clear, non-technical recommendations for product managers and executive leadership.