Analyse product and operational data to generate insights that inform product improvements, workflow optimisation and engagement strategies.
Translate analytical findings into clear, actionable recommendations for product, operations and clinical teams.
Support ad-hoc analysis requests and provide L1 troubleshooting for data-related issues such as dashboard discrepancies or logic mismatches.
Conduct outcome evaluation studies across CHAMP use cases and perform statistical analysis to assess effectiveness.
Prepare evaluation reports, presentations and ensure proper documentation and reproducibility of methods.
Track KPIs such as adoption, engagement and retention identify trends, anomalies and improvement opportunities.
Maintain and enhance dashboards and performance reports support quarterly and annual review cycles.
Develop forecasting and predictive models (e.g. enrolment or usage trends), perform scenario modelling and document assumptions and validation.
Conduct cohort, funnel and behavioural analyses support A/B testing and feature impact assessments.
Maintain an internal knowledge base of recurring issues, solutions and data processes.
Serve as an SME on CHAMP data logic, definitions and data flows maintain structured documentation.
Conduct regular data audits to ensure outputs align with defined logic and evaluation criteria.
Work with IT, data science and product teams to ensure secure, consistent and traceable data processes.
Identify data quality or workflow gaps and propose enhancements for continuous improvement.
Stay updated with best practices in healthcare analytics, product analytics and predictive modelling.
Where appropriate, support selected product-related activities such as contributing data insights for feature refinement and participating in product discussions.
Requirements
Bachelor's degree in Data Analytics, Statistics, Computer Science, Public Health, Health Informatics, or related fields.
Proficiency in Python is required.
Experience with Power BI/Tableau, and familiarity with SQL preferred.
Knowledge of forecasting and predictive modelling techniques is required.
Experience in product analytics (A/B testing, cohort or funnel analysis) is advantageous.
Strong analytical, documentation and communication skills.
Able to work effectively in a dynamic environment with changing programme needs and priorities.
Strong team player who collaborates well across product, data and clinical teams.
Excellent problem-solving, follow-through and attention to detail.
Passionate about using data to improve patient outcomes and population health.
