Data Scientist at The Home Depot in Toronto, ON  M3C 4H9

Pay Range: $95,000 - $125,000

At The Home Depot Canada, we want you to feel valued and supported. The pay range you see represents base salary only. In addition, your total rewards may include: semi-annual bonuses tied to business performance; Deferred Profit-Sharing Program to assist with retirement savings; comprehensive paid benefits; a 15% discount on Home Depot stock purchases; and merit-based salary increases. We are committed to recognizing your efforts and supporting your growth with us.

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Job Description

Title: Data Scientist

Position Overview:

The Data Scientist is a key member of the Advanced Analytics team, responsible for developing and deploying advanced statistical and machine‑learning models that support high‑impact business decisions. This role focuses on transforming large‑scale, complex datasets into predictive insights that improve demand forecasting, inventory decisions, pricing strategies, and overall retail performance.

Key Responsibilities:

Actionable Deliverable: Predictive Modeling & Advanced Analytics

• Design, build, optimize, and maintain scalable, production‑ready forecasting and machine‑learning models.
• Develop time‑series models to predict customer demand at multiple levels of granularity.
• Design and execute “what‑if” scenarios to assess the impact of changes in pricing, promotions, and inventory on demand and profitability.

Actionable Deliverable: Data Preparation & Feature Engineering

• Identify, clean, and engineer features such as seasonality, trends, promotional uplift, cannibalization effects, competitor activity, and macroeconomic drivers.
• Analyze and synthesize large‑scale datasets from multiple internal and external sources to support modeling efforts.

Actionable Deliverable: Collaboration, Deployment & Monitoring

• Partner with business stakeholders to translate business questions into analytical solutions.
• Collaborate with Data Engineering to ensure access to reliable, scalable data pipelines.
• Work with MLOps teams to support model deployment, performance monitoring, and ongoing recalibration as data or business conditions evolve.

Competencies:

• Advanced analytical and quantitative reasoning
• Business partnership and communication

Skills:

• Statistical modeling and machine‑learning techniques
• Data storytelling and insight translation

Direct Manager / Direct Reports:

• Reports to: Manager, Data Science

Travel Requirements:

• Minimal

Physical Requirements:

• Standard office environment; extended computer and data analysis work

Working Conditions:

• Office environment
• In person 5 days a week

Minimum Education:

• Master’s degree or Ph.D. in Data Science, Statistics, Operations Research, Economics, Computer Science, or a related quantitative field
• Equivalent practical experience may be considered

Minimum Years of Work Experience:

• 3+ years of professional experience in data science, analytics, or statistical modeling

Minimum Leadership Experience:

• Not required

Certifications:

• None required

Other Requirements / Assets:

• Strong proficiency in Python and SQL, with experience using common data science libraries (e.g., Pandas, Scikit‑learn, TensorFlow, PyTorch)
• Experience working with cloud platforms, preferably Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage)
• Expertise in time‑series forecasting and statistical modeling techniques
• Experience with optimization methods and algorithms
• Knowledge of retail analytics, including demand forecasting, pricing, inventory, and promotions
• Familiarity with A/B testing, experimental design, and causal inference methodologies
• Ability to communicate complex technical findings to non‑technical stakeholders

In our commitment to efficiency, consistency, and a fair hiring experience for all candidates, The Home Depot Canada uses Artificial Intelligence (AI) technology to assist with the screening and assessment of applicants for this position. This technology is used to quickly and consistently identify candidates whose skills and experience are the strongest match for the role. Our process is designed to ensure human oversight is maintained throughout the selection process.