Note: The job is a remote job and is open to candidates in USA. Giti//c is hiring a Middle Data Analyst to join its analytics team in the iGaming industry. The role owns complex analytical workflows, analyzes player behavior and iGaming KPIs, evaluates A/B tests, applies AI tools, and translates findings into actionable reports for stakeholders.
Responsibilities
- Design and own end-to-end analytical workflows in Amazon Redshift — complex multi-step SQL: window functions, CTEs, large-scale joins, and performance tuning
- Conduct deep-dive player behaviour analyses: segmentation, RFM modelling, cohort analysis, LTV forecasting, and churn prediction
- Analyse A/B test results — interpret statistical significance, evaluate group comparability, identify confounding factors, and deliver clear recommendations to stakeholders
- Track and analyse iGaming KPIs — GGR, NGR, bonus abuse index, deposit/withdrawal trends, player LTV, and churn — proactively flagging anomalies
- Integrate and actively apply AI tools into day-to-day analytical work: prompt engineering, AI-assisted SQL generation, automated insight summarisation
- Translate complex data findings into clear, actionable outputs for non- technical stakeholders via Excel reports and presentations
- Learn and work in EasyMorph for reporting and data preparation tasks as part of team onboarding
Skills
- * 3–4 years of hands-on experience as a Data Analyst in iGaming or online gambling — mandatory
- * Advanced SQL in Amazon Redshift — window functions, CTEs, subqueries, query optimisation, and working with large-scale datasets
- * Experience with BI tools (Power BI, Tableau, Looker, or similar) - working with dashboards and using them to extract insights
- * Proficiency in Excel: advanced pivot tables, vlookups and executive-level reporting
- * Strong command of iGaming KPIs: GGR, NGR, player LTV, churn rate, bonus abuse metrics, deposit/withdrawal volumes
- * Solid understanding of A/B test analysis — interpreting p-values, confidence intervals, and effect sizes; experience evaluating pre-test group balance and flagging randomisation issues
- * Practical use of AI tools in analytical workflows: LLMs for insight generation, AI-assisted querying, prompt engineering for data tasks
- * Strong data quality mindset — ability to sense-check numbers, investigate inconsistencies, and ensure analytical accuracy
- Clear English communication, written and verbal (upper-intermediate+)
- * High ownership and autonomy — you manage your tasks end-to-end without hand-holding
- * Structured analytical thinking — you break down ambiguous business questions into clear data problems
- * Proactive communication — flagging anomalies, pushing back on flawed assumptions, and keeping stakeholders aligned
- * Ability to manage multiple priorities and deliver under deadlines in a fast-paced environment
- * Collaborative mindset — comfortable working across teams and supporting junior colleagues
- * Familiarity with Amazon QuickSight: navigating dashboards, using built-in features (Q / flow), filters, and calculated fields
- * Exposure to EasyMorph or similar ETL/data preparation platforms
Benefits
- Competitive compensation and regular career development reviews
- Flexible working hours and remote options
- Generous vacation and sick leave policy
- Financial assistance for professional development
- Educational Allowances
- Monthly allowance for personal activities
- Comprehensive health insurance plans
- Referral program rewards
- Engaging team-building activities and corporate parties
Company Overview