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