- 2-year contract, renewable
- Government project
- Hybrid work arrangement
What You'll Do
Project scope would include:
- Analyse user engagement patterns and behaviour change across H365 features (Activity Goals, Health & Wellness Challenges) to identify drivers of participation and sustained engagement, leveraging big data from digital apps and wearable devices.
- Evaluate programme effectiveness by applying statistical techniques including hypothesis testing, regression analysis, difference-in-difference analysis, and clustering methods to assess impact on lifestyle behaviours and health outcomes.
- Conduct comprehensive sub-group analysis to identify target audiences and under-served segments, integrating datasets from multiple sources (including SportSG data where relevant) to uncover cross-agency insights and synergies.
- Translate complex analytical findings into clear, actionable recommendations for programme design, marketing strategies and policy decisions, developing compelling visualisations and presentations to communicate insights effectively to diverse stakeholders.
Impact of Your Work
Your analytical outputs will directly support:
- Expanding HealthierSG and H365 programme reach to underserved segments
- Improving participants retention and engagement through data-driven personalisation
- Driving measurable improvements in lifestyle behaviours
- Optimising programme mechanics and incentive structures
Requirement
- Bachelors / Masters degree in Data Science, Statistics, Public Health or related quantitative field from recognised university
- Professional certifications in business analytics / data science from accredited professional bodies coupled with a few years of related working experience for graduates from other disciplines, are also acceptable for the position
- Working experience: Minimally 3 years of experience in business analytics or data analysis roles
- Analytical expertise: Strong foundation in statistical analysis and data interpretation experience with techniques such as hypothesis testing, regression analysis and clustering methods
- Technical proficiency: Proficient in SQL for data extraction and manipulation experience with analytical tools (including Python, Power BI, MS Excel)
- Business acumen: Demonstrated ability to connect data insights with business objectives and translate findings into strategic recommendations portfolio of analytical projects demonstrating impact on business outcomes
- Communication and problem-solving skills: Excellent ability to present complex analytical findings clearly and persuasively to diverse stakeholders, both technical and non-technical self-directed with ability to frame analytical questions, design appropriate methodologies, and derive meaningful insights independently
- Domain knowledge is a plus: Experience in health, fitness or behavioural analytics particularly with digital health platforms, fitness apps, or health programmes familiarity with user engagement metrics, programme evaluation and experimental design experience working with large-scale consumer behaviour or health datasets
