Lead Data Scientist

Join us in re-imagining health care with the largest social enterprise in Canada. 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 drive to ensure that we 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 Data Scientist  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.

Please note this role can be remote or hybrid.

Key Responsibilities
Technical Development

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

Model Development:
Lead end-to-end ML project development including EDA, feature engineering, model selection, training, and validation

Azure ML Implementation:
Oversee design and implementation of ML pipelines using Azure ML, including model deployment, monitoring, and retraining

Statistical Analysis:
Conduct advanced statistical analysis, hypothesis testing, and model validation using appropriate methodologies

Technical Team Leadership

Project Management:
Lead cross-functional ML projects from conception through deployment and monitoring

Peer Review:
Conduct technical reviews of ML models, code quality, and deployment strategies

Lead and mentor data scientists and analysts

Establish technical standards for ML development

Oversee and Collaborate with data engineers on ML pipeline design

Identify and help prioritize machine learning use cases across the organization

Champion adoption of predictive analytics in operations – this includes presenting results, solutions and their application

GoTool Platform Involvement

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

2. Business Analysis & Requirements Leadership
Stakeholder Engagement & Discovery

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

Solution Design & Consulting

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 project lifecycle

Ensure analytical solutions integrate seamlessly with business processes

Measure and communicate business impact of deployed solutions

Required Qualifications
Technical Expertise
Data Science & Machine Learning (Must Have)

Strong statistical knowledge and experimental design

Experience with Azure ML or similar cloud ML platforms is a strong asset

General knowledge of modern BI/analytics platforms

Experience with SQL and data manipulation

Business & Soft Skills
Requirements & Consulting

Proven track record and extensive experience leading requirements gathering for complex analytical projects

Proven track record of translating business needs to technical solutions

Experience with process mapping and workflow analysis

Strong facilitation and workshop leadership skills

Exceptional written and verbal…