Data Analyst

This is a fully remote position, open to applicants in Poland.

📋 Description

• Evaluate player interactions throughout the entire funnel to convert insights into actionable product suggestions;

• Design, execute, and analyze A/B tests and quasi-experimental studies;

• Create and sustain cohort-based analyses to inform product and investment choices;

• Establish, verify, and oversee product KPIs and metric hierarchies;

• Collaborate with product managers to prioritize the development roadmap;

• Create self-service dashboards and data sources;

• Investigate any discrepancies in key metrics;

• Foster a culture of thorough and honest analytics;

• Manage web analytics implementation and ensure data integrity.

⛳️ Requirements

• A minimum of 2 years in Product, Web, or Data analytics;

• Practical experience with web analytics tools (GA4, Amplitude, Mixpanel, or similar), focusing on event design and tracking implementation, beyond just report usage;

• Familiarity with Google Tag Manager or an equivalent tag management system, with the ability to interpret dataLayer specifications and troubleshoot tracking issues;

• Proficient in SQL, including window functions, CTEs, and handling large datasets (experience with Athena or similar is advantageous);

• Solid foundation in statistics: hypothesis testing, confidence intervals, statistical power, and awareness of common experimental pitfalls (like peeking, selection bias, and cohort-maturity bias);

• Experience with funnel analysis, cohort analysis, LTV, and retention modeling;

• Skilled in using a BI tool (preferably Tableau), including designing data sources;

• Knowledge of attribution models and their limitations;

• Proficiency in Python or R for ad-hoc analysis is a plus (pandas, curve fitting, survival analysis);

• At least an Intermediate level of English proficiency (both written and spoken);

• Background in iGaming or another high-frequency B2C sector (such as fintech, gaming, or e-commerce) is a plus.

🏝️ Benefits

• Analyze player behavior across the entire funnel: registration, first deposit, retention, reactivation, and churn, translating insights into actionable product recommendations;

• Design, execute, and interpret A/B tests and quasi-experiments, managing the methodology for assessing feature impact;

• Build and maintain cohort-based analyses (LTV, retention curves, payback) to support product and investment decisions;

• Define, validate, and oversee product KPIs and metric trees, challenging metrics that do not represent genuine business value;

• Collaborate with product managers to prioritize the roadmap based on anticipated impact rather than intuition;

• Develop self-service dashboards (Tableau) and data sources to empower stakeholders to address routine inquiries independently;

• Investigate anomalies in key metrics and effectively communicate root causes to non-technical audiences;

• Promote a culture of thorough and honest analytics: document assumptions, quantify uncertainty, and highlight when data cannot address a question;

• Oversee web analytics implementation and data quality, including tracking plans, event taxonomy, tag management (GTM), and validating new tracking releases.