Partner with product and engineering teams to generate, structure, and validate hypotheses aimed at driving growth and improving user retention
Lead the full A/B testing lifecycle: define success metrics, design experiments, ensure statistical rigor, analyze results, and translate findings into clear business recommendations
Analyze user behavior to identify opportunities for improving LTV, ARPU, and reducing churn
Define, track, and evolve core product and growth metrics aligned with company objectives
Develop dashboards and self-service analytics tools to empower data-driven decision-making across teams
Translate complex data into clear, actionable insights that directly influence product strategy and roadmap decisions.

Strong proficiency in SQL (e.g., Snowflake, Postgres), including use of window functions, CTEs, and efficient query writing
Experience with data visualization tools such as Looker and Superset
Proficiency in at least one scripting language commonly used in analytics (e.g., Python, R)
Strong experience designing, running, and analyzing A/B tests, including power calculations, experiment setup, validation, and interpretation of results
Solid understanding of experimentation methodologies, causal inference, and statistical modeling
Deep understanding of product and monetization metrics such as LTV, ARPU, retention, churn, conversion, and cohort analysis
Strong product thinking: ability to evaluate hypotheses, assess trade-offs, connect metrics to user behavior, and prioritize initiatives based on impact
Experience designing and implementing reliable event tracking systems to ensure data quality and experiment integrity
Excellent communication skills, with the ability to clearly present insights and recommendations to both technical and non-technical stakeholders.

Product Analyst

Key skills