Senior Data Scientist / Toronto, ON (Hybrid) - FTE

Senior Data Scientist

Location: Toronto, ON

Work Model: Hybrid

Experience: 10+

Job Summary

We are seeking an experienced Senior Data Scientist to support the AI Center of Excellence (AI CoE) across machine learning, data science, and advanced analytics initiatives. The ideal candidate will have strong expertise in applied machine learning, statistical modeling, predictive analytics, and data-driven problem solving, with the ability to translate complex business challenges into practical, scalable data science solutions.

This is a highly analytical and hands-on role responsible for delivering end-to-end data science solutions, from data exploration and feature engineering through model development, validation, interpretation, and communication of actionable insights.

Key Responsibilities

• Build, evaluate, and optimize machine learning models, including regression, classification, forecasting, and predictive models.
• Perform data exploration, preparation, cleansing, transformation, and feature engineering to develop high-quality modeling datasets.
• Apply statistical and machine learning techniques to solve complex business and analytical problems.
• Develop and validate models using appropriate model evaluation, experimentation, and statistical methodologies.
• Design and analyze A/B tests and experiments to measure business and product impact.
• Generate actionable insights from structured and unstructured data and communicate findings to technical and business stakeholders.
• Translate business requirements and analytical challenges into practical data science and machine learning solutions.
• Partner with Data Scientists, ML Engineers, Data Engineers, and business teams to move analytical solutions toward production readiness.
• Interpret model results, identify trends and patterns, and communicate recommendations through clear visualizations and presentations.
• Contribute to enterprise AI and analytics initiatives from problem definition and exploration through model development, validation, and production readiness.

Required Skills & Experience

• Strong hands-on experience in Python and SQL.
• Strong knowledge of machine learning, statistical modeling, predictive analytics, and data science methodologies.
• Experience with:
• Regression and classification
• Forecasting and predictive modeling
• Feature engineering
• Model evaluation and validation
• Experimentation and A/B testing
• Data analysis and insights generation
• Strong analytical and problem-solving skills with the ability to work with large and complex datasets.
• Ability to independently manage data science initiatives while collaborating effectively with cross-functional teams.
• Strong communication skills with the ability to explain complex analytical and model outputs to both technical and non-technical stakeholders.

Preferred / Nice-to-Have Skills

• Experience with Azure, Azure Machine Learning (Azure ML), Databricks, MLflow, or similar cloud-based data science platforms.
• Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
• Experience developing solutions for use cases such as:
• Churn prediction
• Customer/member personalization
• Recommendation systems
• Marketing optimization
• Anomaly detection
• Experimentation frameworks
• Experience working with ML model lifecycle management, MLOps, and productionization.
• Experience working in enterprise-scale AI/ML or analytics environments.

Ideal Candidate

The ideal candidate combines strong technical depth in Python, SQL, machine learning, and statistical modeling with strong business problem-solving and communication skills. They should be comfortable working independently, collaborating across data and engineering teams, and delivering data science solutions that can progress from exploration to production.