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.
π 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.
β
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 donβt wait for tasks β you search for insights.
- Flexible thinking and high attention to detail.
π‘ 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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π
$2000-3500
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