Lead, Healthcare Analytics

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Join us in re‑imagining health care with Canada's largest social enterprise. SE Health is leading a multi‑year enterprise transformation project that leverages human‑centered design to be at the forefront of innovation within the healthcare sector. As a leader in home care, we are expanding and enhancing our capabilities to provide personalized experiences using new platforms and cloud‑native architectures, ensuring privacy and security by design.

Our transformation is grounded in guiding principles to prioritize team decisions, long‑term planning, process standardization, data‑driven insights, and balanced user adoption. If you are driven by the desire to have an impact, change the world of health care and shape the future, we invite you to be part of our journey.

SE Health seeks a Lead, Healthcare Analytics to bridge the gap between business needs and advanced analytical solutions. This unique role combines strategic healthcare analytics with data science leadership, requiring someone who can seamlessly transition from stakeholder workshops to Python coding sessions.

The successful candidate will own the end‑to‑end analytics lifecycle – from understanding complex healthcare workflows to deploying data science and machine learning models in production. This position requires proficiency in stakeholder management and technical implementation, leading both the discovery of opportunities and the delivery of solutions. The scope of work includes stakeholder management, requirements gathering, leading workshops, end‑to‑end Data Science and Machine Learning (ML) accountability, data discovery and EDA, creation of compelling data visualizations/reporting, deployment and testing.

This role can be remote or hybrid.

• Guide and mentor exploratory data analysis (EDA) and feature engineering efforts
• Design, develop/code, and validate machine learning models
• Conduct advanced statistical analysis to derive model selection and training
• Lead end‑to‑end ML project development including EDA, feature engineering, model selection, training and validation
• Oversee design and implementation of ML pipelines using Azure ML, including model deployment, monitoring and retraining
• Conduct advanced statistical analysis, hypothesis testing and model validation using appropriate methodologies

• Lead cross‑functional ML projects from conception through deployment and monitoring
• Conduct technical reviews of ML models, code quality and deployment strategies
• Lead and mentor data scientists and analysts
• Establish technical standards for ML development
• Collaborate with data engineers on ML pipeline design
• Prioritize machine learning use cases across the organization
• Champion adoption of predictive analytics in operations – this includes presenting results, solutions and their application

• Manage and evolve the GoTool AI/MLOps platform (our in‑house AI/ML platform)
• Ensure platform reliability and performance
• Drive platform enhancements based on user needs
• Manage quarterly model refreshes and updates
• Coordinate with stakeholders on platform roadmap

• Lead comprehensive requirements gathering using diverse methodologies (workshops, interviews, process mapping, surveys)
• Facilitate analytical discovery sessions with clinical and operational leaders
• Map complex healthcare workflows to identify analytics opportunities
• Build deep understanding of departmental value chains and pain points

• Translate business problems into analytical solution architectures
• Create business cases for predictive analytics initiatives
• Lead end‑to‑end analytical solutions spanning reporting to ML
• Present complex analytical concepts in business‑friendly language
• Develop roadmaps aligning analytics capabilities with business strategy
• Lead cross‑functional analytics projects from conception to value realization
• Manage stakeholder expectations throughout the project lifecycle
• Ensure analytical solutions integrate seamlessly with business…