Senior Data Analyst

Senior Data Analyst Job Level: Senior / Managerial Report to: Head of Business Analyst Location: BGC, Taguig, Philippines Employment Type: Full-time About Us We are a PAGCOR-licensed gaming service provider headquartered in the Philippines. Our company specializes in electronic gaming solutions, including proprietary eCasino content, and partners with multiple integrated resorts across the country. One of our flagship brands, Casino Plus, operates both online and offline gaming platforms. As our business continues to scale, we are looking for a highly analytical and commercially minded Senior Data Analyst to partner closely with Product, Marketing, Operations, User Growth, and other business functions. About the Role The Senior Data Analyst will act as a business problem solver and data partner, rather than simply a reporting or dashboard resource. This role is responsible for deeply understanding business models, identifying problems and opportunities, structuring complex business questions, and translating data into actionable insights and recommendations. The ideal candidate is able to independently take an ambiguous business problem from problem definition → analytical framework → data extraction → analysis → insight → recommendation → business impact. You should be comfortable challenging assumptions, asking the right business questions, and communicating complex analytical findings clearly to both technical and non-technical stakeholders. Experience in Gaming / iGaming, Internet, E-commerce, FinTech, Digital Products, or other data-driven consumer businesses is highly preferred. Key Responsibilities 1. Business Analytics & Problem Solving • Deeply understand assigned business areas, including Platform Marketing, User Growth, Out-of-App/In-Feed Advertising, Game Products, and other key business functions. • Proactively identify business problems, performance gaps, growth opportunities, and potential risks through data analysis. • Translate ambiguous business questions into structured analytical frameworks, hypotheses, key metrics, and actionable analysis plans. • Conduct end-to-end analysis and provide clear recommendations to Product, Operations, Marketing, and business leadership. • Move beyond descriptive reporting to identify why something happened, what it means for the business, and what should be done next. 2. Business Performance & KPI Analysis • Establish and continuously improve business KPI monitoring systems. • Monitor key business metrics, identify abnormal trends, and proactively investigate underlying drivers. • Analyze key gaming and digital business metrics such as revenue, GGR, NGR, user acquisition, retention, conversion, CAC, LTV, ROI, payment performance, and channel efficiency. • Develop user, product, channel, and campaign-level analysis to support business optimization. • Conduct cohort, segmentation, funnel, attribution, and performance analysis where relevant. 3. Special Projects & Strategic Analysis • Independently lead analytical projects from problem definition through final recommendation. • Conduct deep-dive analysis for strategic initiatives such as product launches, user growth, marketing investment, new channels, and business expansion. • Build financial and business models to evaluate commercial opportunities and investment decisions. • Prepare analytical reports and business reviews for senior management. • Quantify the potential business impact of recommendations and track results after implementation. 4. Data Products & Analytics Infrastructure • Participate in the development and optimization of data products, dashboards, and business monitoring systems. • Work with Data Engineering and Product teams to improve data availability, quality, and usability. • Contribute to data warehouse table design, scheduling, data definitions, and ETL processes where required. • Identify opportunities to automate recurring analysis and improve the efficiency of business data usage. • Ensure business KPIs have clear definitions and consistent data standards. 5. Cross-functional Business Partnership • Work closely with Product, Operations, Marketing, User Growth, Data Development, and other business teams. • Challenge business assumptions with data and provide objective recommendations. • Translate complex analytical findings into clear business language for non-technical stakeholders. • Drive data-driven decision-making and support business teams in implementing analytical recommendations. • Build strong relationships with business stakeholders and become a trusted data partner. 6. Data Culture & Methodology • Develop and document analytical methodologies, frameworks, and best practices. • Share analytical approaches and business insights with business teams to improve data literacy. • Promote a data-driven culture across the organization. • Continuously explore new analytical approaches, technologies, and AI-assisted tools to improve analytical efficiency and quality. Requirements