Data Analyst

Data Analyst

Gaming1

Liege, Belgium

YOUR ROLE

• Answering business questions on your player journey with rigorous, well-structured analyses, from data extraction to the final recommendation.
• Building and maintaining the dashboards and reports (Power BI) that your Area relies on day to day, with attention to accuracy and clarity.
• Digging into player behavior — funnels, drop-offs, retention, segmentation — to understand not just what happened, but why.
• Contributing to explorations and Proof of Concepts (including AI) alongside more experienced analysts, to test hypotheses and qualify new approaches.
• Turning your findings into clear, visual deliverables (insight notes, dashboards) that decision-makers can act on directly.
• Working closely with the Head Of, PM, Data Engineers & Data Scientists of your Area, and progressively building that relationship yourself.
• Learning the business inside out: the player journey, the products, the operational realities behind the numbers.

Your mindset

• You are curious by nature and genuinely want to understand how things work, rather than simply producing the requested output.
• You enjoy formulating hypotheses, confronting them with reality, and accepting when facts contradict your initial assumptions.
• You ask questions when something doesn't add up, and you are comfortable saying you don't know yet.
• You don't just deliver a report; you want to understand the actual friction behind player behavior and its root causes.
• You take feedback well and turn it into progress — you want to grow fast, and you know that means being challenged.
• You care about the quality and reliability of your work, and you document what you build.
• You thrive in a team environment and interact daily with various departments to refine your understanding of business reality.

​YOUR PROFILE

• Typically, 1 to 3 years of experience in data analysis, business intelligence or a related analytical role — or a strong first experience such as an internship or a significant academic project.
• Solid SQL skills: you are comfortable writing joins, aggregations and window functions, and eager to grow towards production-grade queries.
• Hands-on experience with a data visualization tool (e.g. Power BI, Tableau) and a willingness to deepen your expertise in semantic modelling and DAX.
• Familiarity with data modelling fundamentals (star schema, basic data quality principles) and an appetite for structured, reproducible work.
• Some exposure to Python for analytical work (data wrangling, exploratory analysis) is a plus.
• An interest in customer or player behavioral data — funnels, retention, segmentation — and in the business questions behind them.
• Professional proficiency in English.
• A degree in Statistics, Mathematics, Economics, Computer Science or a related quantitative discipline, or equivalent practical experience.