Job descriptionData Scientist (Askuity division) at The Home Depot in Toronto, ONM5V 1K4 Job Description Pay Range: $135,000 - $165,000
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.
Are you someone who thrives on helping others succeed, enjoys making an impact, and takes pride in guiding customers to the right solutions for their projects? If you’re also naturally curious and eager to keep learning, consider starting or growing your career with us at The Home Depot. Askuity is a Toronto-based retail analytics software company operating as a division within The Home Depot (THD). Through our supplier analytics program, Askuity’s mission is to enable suppliers and merchants at The Home Depot to make profitable, data-driven decisions and drive real-time execution.
As a Data Scientist on the Askuity team, you will design, build, and deploy advanced analytics and machine learning solutions that drive measurable impact for The Home Depot and its suppliers. You are passionate about turning complex retail, merchandising, and supply chain challenges into data-driven strategies. You thrive in fast-paced environments, balance technical depth with business intuition, and are motivated by seeing your models power real-world retail decisions.
Key Responsibilities
Apply generative AI and retrieval-augmented search to enable natural language analytics and self-serve insights for our users (suppliers and merchants)
Develop predictive and prescriptive models (e.g., anomaly detection, forecasting, regression, classification).
Build, evaluate, and deploy machine learning models in Vertex AI / GCP with production‑grade MLOps practices.
Engineer robust feature pipelines in Airflow and design reusable data products for analytics and ML use cases.
Partner with product managers, merchants, and suppliers to design experiments (A/B testing, causal inference) and measure business impact.
Translate insights into clear, actionable recommendations through visualizations, dashboards (Looker), and storytelling.
Contribute to the evolution of Askuity’s AI strategy by researching and piloting new techniques in time series forecasting, LLM‑based analytics, and Agentic AI.
Drives purpose and vision
Manages complexity
Strategic mindset
Skills
Advanced proficiency in Python (pandas, scikit-learn, TensorFlow/PyTorch) and SQL.
Experience with cloud‑native agentic frameworks (preferably GCP: BigQuery, Vertex AI, Looker).
Strong background in statistical modeling, machine learning, and experimental design.
Familiarity with GenAI/LLMs for analytics, including prompt engineering, RAG, and embedding‑based retrieval.
Experience deploying models and maintaining them through the full MLOps lifecycle.
Direct Manager/Direct Reports
Reports to Sr. Manager, Data Science
Travel Requirements
Limited
Travel to corporate headquarters annually, as requested
Physical Requirements
Extended Sitting
Repetitive Tasks
Working Conditions
Working in an office setting: computer work, camera on virtual meetings
Minimum Years of Work Experience
3+ years
N/A
Certifications
N/A
Other Requirements/Assets
Experience with retail, merchandising, supply chain, or CPG analytics.
Strong communication skills to present complex analyses to technical and non-technical audiences.
Ability to work cross‑functionally with business stakeholders to prioritize and deliver high‑value use cases.
Experience in product management
Contributions to open‑source or applied ML research.
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