Data Analytic / Data Engeneer (gambling) to $3500

We are an international iGaming project operating in Tier-1 markets.
Our product is an online casino with high turnover and ambitious growth plans.

We are currently looking for a strong Data Analyst with a product mindset and iGaming experience, someone who can go beyond "reporting numbers" β€” and instead identify insights, analyze traffic, build funnels and KPIs, and help create a flexible data-driven product strategy.


πŸ” Responsibilities:

  • Analyze player behavior and key product metrics: DAU, MAU, ARPU, ARPPU, LTV, Retention, Churn.
  • Identify anomalies and growth opportunities: quickly spot deviations and trends.
  • Analyze traffic performance by channel (CPA, RevShare, Media Buying, SEO, etc.): from click to FTD, CR, ROI, ARPU.
  • Segment users and traffic sources by value (LTV cohorts, ROI, payback periods).
  • Calculate and visualize key casino KPIs: GGR, NGR, FTD, Conversion Rate, Hold %, Bonus Abuse, etc.
  • Work with affiliate traffic: detect fraud, multi-accounting, low-quality sources.
  • Participate in building ETL pipelines and event-based data models.
  • Write SQL queries and work directly with the replica database (PostgreSQL/MySQL).
  • Build dashboards and reports in BI tools (Metabase, Power BI, etc.).
  • Collaborate with CRM and marketing teams to analyze promo campaigns, email performance, A/B tests, and more.


βœ… Requirements:

  • 1+ year of experience in iGaming / Gambling analytics.
  • Solid understanding of core online casino metrics: FTD, ARPU, LTV, Hold %, Churn, ROI, etc.
  • Confident in SQL: window functions, subqueries, aggregations.
  • Understanding of BI/ETL infrastructure and event-based data models.
  • Strong product mindset: you understand how data drives growth.
  • Skills in data visualization and dashboard building.
  • Comfortable working with raw data and replicas.
  • Proactive approach: you don’t wait for tasks β€” you search for insights.
  • Flexible thinking and high attention to detail.



πŸ’‘ Nice to Have:

  • Experience in grey/growth marketing (arbitrage, affiliates).
  • Knowledge of Python for automation and data processing (Pandas, Jupyter).
  • Experience in building anti-fraud logic, fraud scoring, and behavior analysis.

 

Published 30 June
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