Forecast Analytics Specialist: ML Insights for Merchandising

Canadian Tire Corporation; Toronto; On-site; CAD 53,000 - 88,000; Full time

Job summary

Canadian Tire Corporation is seeking a Forecast Modelling Analyst to drive analytics for merchandising decisions, assortment forecasting and replenishment. You will build predictive models, design actionable reporting, and develop user tools that integrate into business processes.

Role focuses on traditional analytics and ML capabilities, with emphasis on explainable predictions and collaboration across Merchandising, Forecasting and Promotions teams.

Qualifications

• Cross-functional background with strong organizational and project experience.
• 2–4 years in forecasting, analytics, merchandising or supply chain.
• Degree in engineering, math, CS, statistics, business or related field.
• Strong analytical, problem-solving and data-mining skills.
• Programming in Python, SQL or VBA.

Responsibilities

• Collaborate with Merchandising, Forecasting and Promotions to ensure model predictions align with business intuition.
• Design and build user-friendly tools and reporting.
• Plan and manage multiple work requests, from ad-hoc analyses to long-term projects.
• Ensure forecasting systems, reports and EUC tools are operational and enhanced.
• Apply traditional analytics and predictive modelling to identify drivers and scenarios.
• Serve as SME for Forecasting processes and guide special projects.

Skills

Python

SQL

VBA

Excel

Microsoft Access

Data mining

Machine learning

Visualization

Communication

Project management

Education

University degree in engineering, math, computer science, statistics, business or related field

Tools

Database systems

Job description

Canadian Tire Corporation is seeking a Forecast Modelling Analyst to drive analytics for merchandising decisions, assortment forecasting and replenishment. You will build predictive models, design actionable reporting, and develop user tools that integrate into business processes.

Role focuses on traditional analytics and ML capabilities, with emphasis on explainable predictions and collaboration across Merchandising, Forecasting and Promotions teams.