Forecast Modelling Analyst at Canadian Tire Corporation, Limited in Toronto, ON

Job description

What you’ll do: The Forecast Modelling Analyst performs analysis and generates insights that can be integrated into key merchandising decisions (assortment selection, product forecasting and replenishment). You will conduct traditional and machine learning analytics to identify and quantify cause-and-effect relationships, design/issue digestible reporting, and develop/optimize user tools. You will play a key role in the delivery of our advanced analytics roadmap and development of predictive modelling/machine learning capabilities, while continuing to support the business with traditional analysis and established processes. The primary responsibilities of this role include: Work with the Merchandising, Forecasting, and Promotions teams to ensure model predictions are consistent with business intuition, explainable and efficiently integrated into processes Design and build tools/reporting that is user friendly and actionable Plan, track and manage multiple work requests – these initiatives can range from quick ad-hoc analysis requests, urgent system/tool support issues, or medium-scale process improvement initiatives or formal long-term project implementations Ensure the forecasting systems, reports and EUC tools are operational and support the business processes; lead projects to implement new functionality, including automation Use traditional analytics and predictive/statistical modelling techniques to identify and quantify sales drivers, conduct what-if scenario analysis and measure the causal impact of results Act as a subject matter expert for Forecasting processes and provide expertise and direction in special projects What you bring: The dynamic environment requires individuals with a cross functional background, excellent organizational skills, experience working in a project environment, advanced analytical ability, strong communication skills and the ability to work effectively in a team as well as independently. 2-4 years work experience in various roles within forecasting, analytics, merchandising or supply chain. University degree in engineering, math, computer science, statistics, business or related field. Strong analytical, problem solving, and data mining skills with the ability to summarize and deliver actionable insights or recommendations. Programming experience with Python, SQL, or VBA. Advanced technical skills in Microsoft Access, Excel, Database systems. Passion for data sciences, machine learning, and visualizations. Cloud experience is an asset. Results-oriented, with proven project and time management skills (planning, prioritizing, executing, and tracking). Business mindset with an understanding of the retail industry. Effective written and verbal communication skills, including presentation abilities. We’re always looking for great talent! In addition to competitive pay, we offer: Comprehensive benefits and retirement programs Continuing Education Programs Other perks to support your well-being Career growth opportunities and product discounts Broadband Salary Range: $53,000 – $88,000. Our typical hiring range is between $53,000 and $70,000. Salary decisions are also dependent on other factors such as your experience, industry benchmarks, internal equity and other role-specific requirements. For critical roles, the compensation offering will be reviewed to ensure alignment with market rate and conditions and the unique value you bring to the role. #LI-MM3 This posting represents an existing vacancy within our organization. We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters. About Us Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, over 1,600 retail locations, financial services, exemplary e-commerce capabilities, and exciting market-leadin