Senior Data Scientist: Predictive Analytics & Impact

Canadian Tire Corporation, Ltd.; Toronto; On-site; CAD 64,000 - 106,000; Full time

Job summary

Canadian Tire Corporation, Limited is hiring a Senior Data Scientist, Predictive Modelling to build predictive and prescriptive models that inform enterprise decisions such as product forecasting, replenishment, pricing, and promotions. You will apply ML and traditional analytics to quantify causal impact and deliver data-driven insights.

You will work with cross-functional teams, manage multiple projects, and lead model implementations while mentoring peers.

Qualifications

• 4+ years work experience in data science, modelling, and analytics (merchandising or supply chain preferred).
• University degree (graduate preferred) in engineering, math, computer science, statistics, business or related field.
• Proficiency with programming in Python, PySpark, SQL.
• Experience with data science disciplines, including machine learning, data transformation/engineering, data validation, visualization, and productionizing projects.
• Experience with Cloud computing environments for data science. Knowledge of Azure and Databricks would be an asset.

Responsibilities

• Develop predictive and prescriptive solutions for enterprise decisions (product forecasting, replenishment, pricing, promotion optimization).
• Perform traditional analytics and ML to quantify cause-and-effect relationships.
• Lead multiple projects, plan and track initiatives from long-term programs to quick ad-hoc analyses.
• Provide data-supported insights to improve forecasts and business decisions.
• Act as a subject matter expert for established models and methodologies.

Skills

Python

PySpark

SQL

Data analysis

Forecasting

Education

University degree in engineering/math/CS/statistics/business or related field

Tools

Azure

Databricks

Job description

Canadian Tire Corporation, Limited is hiring a Senior Data Scientist, Predictive Modelling to build predictive and prescriptive models that inform enterprise decisions such as product forecasting, replenishment, pricing, and promotions. You will apply ML and traditional analytics to quantify causal impact and deliver data-driven insights.

You will work with cross-functional teams, manage multiple projects, and lead model implementations while mentoring peers.