What you’ll do
We’re looking for an Applied ML Lead Scientist who blends predictive modelling & complex analysis with AI strategy and scalable delivery. You will own high-impact models (forecasting, optimization, causal inference) and shape the patterns, platforms, and guardrails that let teams ship AI at scale (agentic workflows, MLOps). You’ll partner across Merchandising, Dealers, and Engineers to turn models into value, deployment faster, create reusable components, and measurable business outcomes.
Outcomes & KPIs (what success looks like)
· Business impact: Incremental sales & margin lift, markdown recovery ratio, inventory turns, stock-out reduction.
· Model performance: Forecast/optimization accuracy, causal validity, lift vs. baseline, drift & stability metrics.
· Scale & reuse: # of workloads on common patterns (feature/embedding stores), service reliability (SLOs), time-to-production.
· Adoption & enablement: Utilization of ML/AI features in Merch/Stores workflows, stakeholder satisfaction, training coverage.
· Governance & risk: Policy conformance, evaluation/guardrail incidents prevented, cost-to-value adherence.
Key Responsibilities
1) Predictive Modelling & Decision Science
- Lead development of forecasting, price/markdown/assortment optimization, propensity and uplift models.
- Design experimentation & causal inference (A/B, quasi-experiments, synthetic controls) to prove impact.
- Translate complex analysis into clear decisions and playbooks for Merch, Stores, and Dealer partners.
2) AI Strategy & Scaling
- Define applied AI technical direction for priority initiatives (agentic systems, recommendations).
- Establish reusable patterns (prompt/agent orchestration, retrieval, evaluation) and champion platform leverage (e.g., feature/embedding stores, registries).
3) Agentic AI & Applications
- Guide the build of task-oriented agents and pipelines that combine reasoning, tool use, and workflow automations.
- Integrate agents into business surfaces (e.g., Teams apps, dashboards, operational tools) with safe autonomy and observability.
4) MLOps, Reliability & Cost
- Partner with Engineering to productionize models/services (CI/CD, serving, monitoring, evals, rollback).
- Partner with QA teams to measure and optimize latency, availability, cost-to-value, and model lifecycle
5) Governance & Risk Management
- Partner with governance teams to embed AI/DS governance (data use, privacy, safety, bias, evals) into development and release processes.
- Guide team to document decisions, assumptions, and model cards; drive remediation when risks surface.
6) Leadership & Influence
- Lead cross-functional delivery with notable complexity/risk; mentor DS peers and analysts.
- Persuade senior stakeholders with crisp narratives and quantified trade-offs
What you bring to the team
- 5+ years across data science & ML, including retail/operations use-cases (or adjacent large-scale domains).
- Deep fluency in Python/SQL, classical ML, time-series, optimization, causal inference, and experimentation.
- Practical experience with LLMs/RAG (prompt/agent orchestration, retrieval design, evals/guardrails).
- Hands-on MLOps (serving, monitoring, drift detection, model registries, CI/CD) on a modern cloud stack.
- Experience with Databricks/MLflow/feature stores; vector DBs; cost/perf tuning for AI workloads.
- Prior work building agentic or workflow-automation systems.
- Track record influencing at VP/SVP levels, translating technical complexity into business outcomes.
Our typical hiring range is between $79,000.00 - 131,000.00 CAD Annual. 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.
This posting represents an existing vacancy within our organization.
About Us:
Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, 1,700 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. We invest in new technologies and products while 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 savings programs for eligible employees.
Core Values:
We are innovators and entrepreneurs at our core; outcomes drive us; inclusion is a must; we are stronger together; 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—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, or 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, among others. Should you require any accommodation in applying for this role or throughout the interview process, please make them known when contacted so we can work with you to meet your needs.
Job Type: Full-time
Pay: $79,000.00-$131,000.00 per year
Benefits:
- Dental care
- Disability insurance
- Employee assistance program
- Extended health care
- Flexible schedule
- Life insurance
- Paid time off
- Store discount
- Tuition reimbursement
- Vision care
- Wellness program
Work Location: In person
