Product Data Analyst

The expertise we’re looking for:

• 3+ years in product or data analytics.
• Strong SQL: complex joins, window functions, query performance on large datasets (ClickHouse experience is a plus).
• Hands-on experience with at least one BI tool (QuickSight, Power BI, Tableau or similar).
• Solid understanding of statistics for experiments: significance, power, common pitfalls such as peeking and multiple comparisons.
• Python or R for analysis beyond what SQL covers.
• Ability to explain findings to non-analysts in plain language
• English (B2 or higher).

Would be a plus:

• iGaming experience and familiarity with core metrics: GGR (gross gaming revenue, total bets minus total wins), RTP (return to player, the share of bets paid back as wins), bet volume, retention.
• Experience with data quality checks or building data pipelines.

Your responsibilities will include:

• Own analytics for a set of games or a product area: KPIs, regular reporting, deep dives into player behaviour.
• Design and analyse A/B tests for game mechanics and features, from hypothesis and sample size to the final read-out.
• Build and maintain dashboards in QuickSight / Power BI on top of data in ClickHouse.
• Work with game designers, product managers and data engineers to define metrics and make sure tracking is correct.
• Take part in improving our BI setup, including data models and reporting migration.

What we expect:
We are looking for someone who treats an analytical area as their own, not as a queue of tickets. In practice that means:

• You take a question from a stakeholder and work out what decision it is meant to support, before you write any SQL.
• You notice when a number looks wrong (in your report or someone else’s) and chase it to the root cause instead of passing it on.
• You keep your dashboards and data pipelines alive after release: you know who uses them, check that they still show correct data, and retire what nobody needs.
• You raise problems and trade-offs early, with a proposed way forward, rather than waiting to be asked.
• You finish things: a piece of analysis ends with a clear conclusion and a recommendation, not just a table.