Lead Data Scientist to bridge gap business and advanced analytical solutions Job Ottawa area,Ontario Canada,IT/Tech

Position: Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions

Our healthcare client is seeking a Lead Data Scientist to bridge the gap between business needs and advanced analytical solutions

This is a full time permanent position. Hybrid work model 1-2 times a month on site in Markham, ON. Open to fully remote if located outside of the GTA.

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

Must Haves:

Data Science & Machine Learning

Python programming (
Num Py, Pandas, Scikit-learn, Tensor Flow/Py Torch )

Experience leading discovery shops is mandatory (not just getting requirements from BAs)

Strong statistical knowledge and experimental design

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

Model lifecycle management experience

Python, Pandas, Geo Pandas

Analytics & BI Understanding

General knowledge of modern BI
/analytics platforms

Experience with SQL and data manipulation

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

Key Responsibilities:

1. Data Science & Machine Learning Leadership

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

Project Leadership

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


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