Develop, validate, and deploy advanced machine learning, statistical, and AI models (descriptive, predictive, prescriptive, supervised, and unsupervised) to support strategic, operational, and policy decision making across the organization.
Engage with clinical, business, and cross unit stakeholders to understand needs, identify opportunities, and frame, prioritize, and deliver high impact analytics and data science driven use cases.
Conduct exploratory data analysis, feature engineering, and advanced analytics on structured and unstructured healthcare and administrative data to generate actionable insights, scenarios, and forecasts.
Collaborate closely with Data Engineering, platform, and architecture teams to ensure reliable, secure, high quality data pipelines and seamless operationalization of analytical models into production systems.
Work with Data Governance, Privacy, Security, and Quality teams to ensure compliance with health data regulations, ethical AI principles, data standards, and internal policies.
Design and execute robust model evaluation and validation processes, including hypothesis testing, bias and fairness assessments, A/B testing, sensitivity analysis, and ongoing performance monitoring.
Conduct market and technology scanning to stay current with emerging data science trends, tools, and healthcare analytics innovations, and assess their relevance and potential value to the organisation
Lead research efforts to explore new data sources, analytical techniques, and AI tools, and provide strategic guidance on adopting data driven innovations that enhance organizational outcomes.
Translate complex analytical results into executive ready insights, dashboards, policy briefs, and presentations to support leadership, planning, and evidence based decision making.
Serve as a thought leader by contributing to internal capability building, mentoring, knowledge sharing, and representing the organization through presentations, publications, or analytical forums when appropriate
Undertake all duties and responsibilities reasonably required and aligned with the data management & governance.