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CT
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- Full-time
Reporting to the AVP, Advanced Analytics and Modelling, the Manager, Statistical Modelling & Advanced Analytics will lead high-impact statistical modelling work that helps shape decisions…
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Canadian Tire Corporation

Manager, Statistical Modelling & Advanced Analytics

Toronto, ON, Canada

Our typical hiring range is between $80,000.00 and $140,000.00 per annum. · Full-time

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Job details

Pay: Our typical hiring range is between $80,000.00 and $140,000.00 per annum.
Job type: Full-time
Apply by: Nov 14, 2026
Posting language: English
Posted: Oct 21, 2026

Original job description

Reporting to the AVP, Advanced Analytics and Modelling, the Manager, Statistical Modelling & Advanced Analytics will lead high-impact statistical modelling work that helps shape decisions across retail, customer, and loyalty. This role is ideal for someone who enjoys solving complex business problems with rigorous quantitative methods and translating that work into real business action.

You will have the chance to directly impact customer growth and retention, promotional effectiveness, and strategic retail decision-making. You’ll have the chance to work with large, complex datasets and influence decisions that matter across the enterprise.

What you’ll do

Lead the design and development of advanced statistical and quantitative models using retail, customer, and loyalty data
Apply methods such as forecasting, causal inference, experimentation, predictive modelling, segmentation, optimization, and statistical learning to solve important business problems
Partner closely with business leaders to identify where modelling can most improve decision-making, customer outcomes, and financial performance
Build models and analytical frameworks that are practical, scalable, and decision-oriented
Establish strong standards for model design, validation, monitoring, and measurement
Translate complex quantitative work into clear recommendations for senior leaders
Help shape the future of modelling and experimentation within the broader analytics organization
Coach and develop a team of analysts and data scientists, while remaining close to the work and setting a high bar for technical quality

What you bring

Graduate degree in Statistics, Mathematics, Econometrics, Economics, Data Science, Computer Science, or another quantitative field
PhD is welcome, but not required
Significant experience in statistical modelling, advanced analytics, or quantitative decision support
Strong command of methods such as:
- Regression and classification
- Forecasting / time series
- Experimental design and measurement
- Causal inference
- Statistical learning
- Model validation and performance assessment
Strong coding experience in Python
Experience working with large datasets using SQL, Spark, or similar tools
Experience in modern data environments such as Databricks, cloud platforms, or distributed computing frameworks
Strong communication skills, with the ability to explain technical work clearly to non-technical audiences
Experience leading projects, influencing senior stakeholders, and helping others raise the quality of their work
In addition to the above qualifications, preference will be given to candidates who have:
- Experience in retail, loyalty, consumer, pricing, marketing, or customer analytics
- Experience with experimentation platforms, uplift modelling, optimization, or decision science
- Experience building modelling workflows that move beyond analysis into operational use

We’re always looking for great talent! In addition to competitive pay, we offer:

Comprehensive benefits and retirement programs
Performance incentives, Continuing Education Programs
Other perks to support your well-being
Career growth opportunities and product discounts

Our typical hiring range is between $80,000.00 and $140,000.00 per annum. Salary decisions are also dependent on other factors such as your experience, job-related knowledge, skills and competencies, market location, industry benchmarks, internal equity and other role-specific requirements. We're committed to attracting top talent. 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.

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-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees. As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees. Join us in helping to make life in Canada better through living and working our Core Values: we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility. It is an especially exciting time to join CTC and its family of companies where career opportunities are wide-ranging! Join us, where there's a place for you here.

Our Commitment to Diversity, Inclusion and Belonging

We are committed to fostering an environment where belonging thrives, and diversity, inclusion and equity are infused into everything we do. We believe in building an organizational culture where people are consistently treated with dignity while respecting individual religion, nationality, gender, race, age, perceived ability, spoken language, sexual orientation, and identification. We are united in our purpose of being here to help make life in Canada better.

Accommodations

We stand firm in our Core Value that inclusion is a must. We welcome and encourage candidates from equity-seeking groups such as people who identify as racialized, Indigenous, 2SLGBTQIA+, women, people with disabilities, and beyond. Should you require any accommodation in applying for this role, or throughout the interview process, please make them known when contacted and we will work with you to help meet your needs.

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More about this job

Responsibilities

The manager will lead the design and development of advanced statistical models to drive retail, customer, and loyalty decision-making. They will partner with business leaders to translate complex quantitative insights into actionable recommendations while coaching a team of analysts.

Requirements

Candidates must possess a graduate degree in a quantitative field and significant experience in statistical modelling or advanced analytics. Strong proficiency in Python, SQL, and modern data environments like Databricks is required, along with experience leading projects and influencing stakeholders.

Skills

Statistical modelling
Advanced analytics
Python
SQL
Spark
Forecasting
Causal inference
Experimental design
Predictive modelling
Segmentation
Optimization
Statistical learning
Databricks
Cloud platforms
Distributed computing
Data science

Benefits

Comprehensive benefits
Retirement programs
Performance incentives
Continuing education programs
Product discounts
Mental health benefits
Profit sharing

Visa sponsorship

Not detected in the job text

Keywords

Statistical Modelling
Advanced Analytics
Retail Analytics
Customer Analytics
Loyalty Data
Python
SQL
Spark
Databricks
Cloud Platforms
Distributed Computing
Forecasting
Causal Inference
Experimental Design
Predictive Modelling
Segmentation
Optimization
Statistical Learning
Model Validation
Econometrics
Data Science
Decision Science
Uplift Modelling
Marketing Analytics
Pricing Analytics
Quantitative Methods
Leadership
Stakeholder Management
Data Frameworks
Operational Use

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