Corporate Strategy - Data Science Implementation Analyst/Consultant

Work that powers communities

Who We Are

Singapore Pools was established by the Singapore government on 23 May 1968 to provide safe and trusted betting to counter illegal gambling. As a not-for-profit organisation, it makes contributions to the Tote Board to fund a wide range of causes in social service, community development, sports, arts, education and health sectors.

Since 2004, over $5 billion have been channelled to the Tote Board. In addition, Singapore Pools also contributes about $2 billion annually to the Government in the form of taxes and duties. Its responsible gaming practices have been awarded the highest level of certification (Level 4) by the World Lottery Association’s Responsible Gaming Framework since 2012.

Since inception, Singapore Pools’ staff have a long-standing commitment to doing good and giving back to those in need. Staff volunteers support activities held all year round, from helping disadvantaged children, youth-at-risk, underprivileged families, and elderly, to conserving the environment.

Job Purpose

Reporting to the Senior Manager, the incumbent will develop and implement data processing pipelines, modelling workflows, and tools to support key strategic initiatives.

What You'll Do

• Identify, undertake, and implement analytics projects in collaboration with strategy team members and technical stakeholders.
• Translate agreed analytical and modelling requirements into well‑structured, efficient, and maintainable code within defined scope and timelines.
• Support end‑to‑end implementation of analytical frameworks and models, with emphasis on code quality, reproducibility, robustness, and performance.
• Maintain and refine existing analytical models and pipelines to ensure continued relevance, accuracy, and operational stability.
• Contribute to the productionisation and operational deployment of analytics and models, including automation, scheduling, monitoring, documentation, and version control.
• Support the development of Singapore Pools (SPPL)’s in house analytics capabilities through adoption of structured methodologies and reusable technical frameworks.
• Promote good software engineering practices within the data science team, including code reviews, testing standards, documentation, and knowledge sharing.
• Support technical integration and implementation of agreed analytical approaches with internal teams and external partners.
• Support the strategy team by implementing analytics and modelling solutions that enable execution of SPPL’s long‑term strategic initiatives.
• Collaborate closely with strategy team members and technical stakeholders to own and implement analytical and modelling requirements through well‑structured, efficient, and maintainable code, within agreed project scope and timelines.
• Collaborate with strategy and business stakeholders to ensure analytical outputs are fit‑for‑purpose and decision‑relevant.
• Provide technical and analytical support to strategy‑led projects involving regulators, industry partners, or international lottery operators.

Who You Are

• Postgraduate degree in Data Science, Computer Science, Machine Learning, or a related quantitative field.
• Demonstrated experience building, deploying, and operating data science or ML models in production.
• Strong Python skills, with hands-on experience building advanced data analytics / ML models and exposure to LLMs.
• Working knowledge of SQL and PySpark for large-scale data processing and model pipelines.
• Strong engineering fundamentals: data structures & algorithms, Git/version control, testing, API design, and CI/CD.
• Deployment experience with Docker / Docker Compose / Portainer on Linux/Unix, across on-prem and/or cloud.
• Hands-on experience with GPU-enabled environments for ML training and inference, with working proficiency in Unix/Linux for development, deployment, and production troubleshooting.
• Experience with cloud data and ML platforms (e.g., AWS, Snowflake, Azure).
• Experience building user-facing applications with Python web frameworks (e.g., Django) and front-end (HTML/CSS/JS, React) is a plus.

What We Offer