Senior Data Analyst — AI-Driven Insights (Remote)

RubyPlay

Warszawa

Remote

PLN 180,000 - 260,000

Full time

3 days ago

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Benefits offered by this job

Remote-first

Learning budget

Health coverage

Yearly bonus

Career growth

Global team

Job summary

RubyPlay, Warsaw (Remote), seeks a Senior Data Analyst to lead end-to-end analysis across commercial and product domains. You will own metrics, build AI-powered tools, and contribute to a unified semantic layer, enabling self-serve insights for the business.

You’ll partner with finance, marketing, and engineering to drive data-informed decisions. You should have 5+ years in data analysis, 2+ years in a senior role, strong SQL in Snowflake, Python for automation, and hands-on AI experience.

Qualifications

5+ years as a data or business analyst, including at least 2 years in a senior role owning a domain end to end and presenting to senior management.
B2B iGaming experience: at least 2 years as an analyst at a game provider, aggregator, platform or other B2B iGaming company, with working knowledge of GGR, RTP, operators, aggregators and regulated vs. unregulated markets.
Hands‑on experience building with AI: AI tools are a core part of your daily work, and you have built AI skills, plugins or agents that automate analysis or workflows for yourself and others.
Expert SQL on large datasets in a cloud data warehouse (Snowflake or similar).
Python for analysis and automation.
Strong business judgement: you separate signal from noise and can explain why a number moved, not only that it did.
Clear executive communication: you turn complex analysis into a short, plain-language recommendation.

Responsibilities

Lead ad-hoc and recurring analysis across the business, primarily commercial and product: operator and market performance, revenue drivers, game and portfolio performance, player KPIs and retention.
Explain what drives changes in revenue (GGR) and turn findings into concise, decision-ready reports and presentations for senior management.
Build AI skills, plugins and agents that automate analysis, monitoring and reporting, and make them available to business users.
Define and maintain metrics and business logic in the semantic layer, so the company works from one set of definitions.
Replace manual recurring analysis with automated, self-serve outputs and alerts.
Own data quality in your domains: identify issues, trace them to the source and fix the definitions behind them.