This job posting has expired
Expired on April 1, 2026
Job Description
The Data Analyst is responsible for ensuring product stability and driving growth by continuously monitoring key metrics, detecting anomalies, and performing deep-dive analyses to uncover the drivers behind performance shifts. This role is not about building data pipelines; it is about analytical investigation. You will focus on understanding the "why" behind the data—identifying what broke, what worked, and providing actionable insights to optimize results.
Responsibilities
- Continuously track key product and business KPIs to ensure data health
- Identify deviations from expected values and ensure timely, accurate reporting
- Maintain the integrity of analytical dashboards
- Investigate drops or fluctuations in metrics to distinguish symptoms from core issues
- Conduct deep-dive analyses to explain performance changes and provide clear, data-backed answers
- Establish the root causes of performance shifts rather than just reporting symptoms
- Establish benchmarks based on historical data to evaluate current performance
- Compare results against internal standards to identify opportunities for growth and optimization
- Track performance trends over time to predict potential risks
- Translate complex data sets into clear, narrative insights for stakeholders
- Highlight both "red flags" and success stories, proposing specific actions to improve KPIs
- Turn raw data into actionable business strategies
- Partner with Product, Marketing, and Finance teams to align analytics with business objectives
- Empower teams to make data-informed decisions through clear communication
- Help stakeholders better understand data trends and their direct impact on the business
Qualifications
- 2+ years of experience as a Data, Product, or Performance Analyst in iGaming
- Solid understanding of product and business metrics (KPIs, Funnels, Retention, Revenue, Conversion, etc.)
- Proven track record in troubleshooting metric drops, analyzing instability, and identifying root causes
- Strong command of SQL (PostgreSQL / BigQuery), including complex queries, joins, and aggregations
- Experience building and maintaining dashboards in Tableau, Looker Studio, or similar tools
- Practical experience using Python for data analysis (Pandas, Numpy)
- Advanced proficiency in Excel / Google Sheets for rapid data validation and hypothesis testing