Product Data Analyst

Role overview

Own analytics for a portfolio of games or a product area, turning behavioral and performance data into decisions for product teams. The work spans KPI definition, recurring reporting, deep-dive analysis, experiment design, dashboard maintenance, and improvements to data models and business intelligence workflows.

Responsibilities - Define and monitor product KPIs, produce regular reporting, and investigate player behavior and performance changes. - Design and evaluate A/B tests, from shaping hypotheses and estimating sample sizes to interpreting and communicating results. - Build and maintain dashboards using business intelligence tools over analytical data sources. - Work with product managers, designers, and data engineers to define metrics and ensure event tracking is accurate. - Contribute to improvements in BI infrastructure, data models, and reporting migrations. - Validate unexpected results, maintain useful dashboards and pipelines, and conclude analyses with clear recommendations.

Requirements - At least three years of experience in product or data analytics. - Strong SQL skills, including complex joins, window functions, and performance tuning on large datasets. - Hands-on experience with a BI tool such as QuickSight, Power BI, Tableau, or an equivalent. - Sound statistical knowledge for experiments, including significance, power, and risks such as repeated checking and multiple comparisons. - Ability to use Python or R for analysis beyond SQL and explain findings in plain language. - English proficiency at B2 level or higher.

Nice to have - Familiarity with gaming metrics such as gross gaming revenue, return to player, betting volume, or retention. - Experience with ClickHouse, data quality checks, or building data pipelines.

Benefits and work setup - Flexible working hours, legal support, and access to a corporate psychologist. - Gifts for significant occasions and opportunities to share ideas with senior leaders and drive business changes.