Senior Executive/Assistant Manager, AIO - CHAMP (2 years contract)

National University Polyclinics; Singapore; On-site; SGD 80,000 - 100,000; Part time

Job summary

A leading healthcare institution in Singapore is looking for a Senior Executive/Assistant Manager for their AIO initiative. This role involves analyzing product data to enhance workflow and engagement strategies, developing predictive models, and supporting ongoing product-related activities. Candidates should possess a background in Data Analytics, proficiency in Python, and experience with visualization tools like Power BI or Tableau. This position offers an opportunity to significantly impact patient outcomes by leveraging data insights.

Qualifications

• Bachelor’s degree in Data Analytics, Statistics, or related fields.
• Proficiency in Python required.
• Experience with Power BI/Tableau preferred.

Responsibilities

• Analyse product and operational data to generate insights.
• Translate analytical findings into actionable recommendations.
• Conduct outcome evaluation studies and perform statistical analysis.

Skills

Proficiency in Python

Analytical skills

Strong communication skills

Collaboration across teams

Problem-solving

Education

Bachelor’s degree in Data Analytics, Statistics, Computer Science, Public Health, or related fields

Tools

Power BI

Tableau

SQL

Job description

Senior Executive/Assistant Manager, AIO - CHAMP (2 years contract)

Job Function: Administration

Institution: National University Health System

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.

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.