Data Scientist (Askuity division)

The Home Depot•Toronto, ON

1d•$62,200 - $70,100•Onsite

About The Position

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.

Requirements

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.
Undergraduate degree in a quantitative field
3+ years of work experience
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.

Nice To Haves

Experience with retail, merchandising, supply chain, or CPG analytics.
Experience in product management
Contributions to open-source or applied ML research.

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.