Data Analyst – Player & Business Performance

Data Analyst – Player & Business Performance Job Summary We are looking for a Data Analyst to turn player, marketing, CRM, and business data into actionable insights that support acquisition, retention, and revenue growth. The role will focus heavily on player behaviour, FTD, retention, deposits, NGR, LTV, campaign performance, and business performance analysis . Candidates with experience in high-volume digital platforms, online entertainment, fintech, gaming, or similar industries will be highly preferred. Key Responsibilities Analyze player behaviour and lifecycle performance , from registration and FTD to retention and reactivation. Monitor key business metrics including FTD, Deposits, GGR/NGR, LTV, Retention Rate, Churn Rate, ARPU/ARPPU, CPA and ROAS . Analyze acquisition channels and identify differences in player quality, conversion, retention, and long-term value. Perform player segmentation based on deposit behaviour, activity, value, lifecycle stage, and engagement. Support CRM and Retention teams by identifying high-value, inactive, churn-risk, and reactivation player segments. Analyze campaign and promotion performance to determine impact on deposits, activity, retention, and revenue. Identify unusual trends, performance drops, growth opportunities, and changes in player behaviour. Build and maintain daily, weekly, and monthly performance dashboards and reports. Conduct deep-dive analysis to explain why KPIs increased or decreased , rather than only reporting the numbers. Translate complex data into clear business insights and actionable recommendations for Management, Marketing, CRM, Product, and Operations teams. Work closely with cross-functional teams to improve data accuracy, reporting standards, and business decision-making. Requirements Strong hands-on experience with SQL . Strong Excel / Google Sheets skills. Experience with Power BI, Tableau, Looker Studio, or similar BI tools . Strong analytical and problem-solving skills. Able to work with large datasets and identify meaningful trends and patterns. Good understanding of customer lifecycle, acquisition, retention, and revenue analysis. Able to communicate analytical findings clearly to non-technical stakeholders. Experience with Python, BigQuery, Snowflake, or similar data tools will be an advantage. Added Advantage Experience working with metrics such as: FTD | GGR | NGR | Deposits | LTV | Retention | Reactivation | Churn | VIP Segmentation | CPA | ROAS | Player Acquisition Experience in online entertainment, gaming platforms, fintech, high-volume digital products, CRM, or performance marketing analytics will be highly preferred.