Assistant Manager, AIO CHAMPS

Key Responsibilities

• 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.

Qualifications & 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.