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The Home Depot

Data Scientist (Askuity division)

Toronto, ON, Canada

The pay range for this position is between $62,200.00 - $70,100.00

Apply About employer

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Job details

Pay: The pay range for this position is between $62,200.00 - $70,100.00
Posting language: English · French
Posted: Aug 31, 2026

Original job description

English section of this bilingual listing.

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.

Competencies:

Drives purpose and vision
Manages complexity
Strategic mindset
Drives engagement
Collaborates

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

Reports to Sr. Manager, Data Science

Physical Requirements:

Extended Sitting
Repetitive Tasks

Working Conditions:

Working in an office setting: computer work, camera on virtual meetings

Minimum Education:

Undergraduate degree in a quantitative field

Minimum Years of Work Experience:

3+ years

Minimum Leadership Experience:

Certifications:

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.

------------------------------------------------------------------------

Description du poste

The pay range for this position is between $62,200.00 - $70,100.00

Read the full bilingual original

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.

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.

Competencies:

Drives purpose and vision
Manages complexity
Strategic mindset
Drives engagement
Collaborates

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

Reports to Sr. Manager, Data Science

Physical Requirements:

Extended Sitting
Repetitive Tasks

Working Conditions:

Working in an office setting: computer work, camera on virtual meetings

Minimum Education:

Undergraduate degree in a quantitative field

Minimum Years of Work Experience:

3+ years

Minimum Leadership Experience:

Certifications:

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.

------------------------------------------------------------------------

Description du poste

Basée à Toronto, Askuity est une entreprise offrant une plateforme logicielle d’analyse en commerce de détail qui exerce ses activités en tant que division de Home Depot. Par l’entremise du programme d’analyse des fournisseurs, sa mission est de permettre aux fournisseurs et aux négociants de Home Depot de prendre des décisions rentables fondées sur des données et d’assurer l’exécution des initiatives en temps réel.

À titre de scientifique des données au sein de l’équipe d’Askuity, le titulaire de ce poste conçoit, élabore et déploie de l’analytique avancée ainsi que des solutions d’apprentissage automatique qui auront une incidence mesurable pour Home Depot et ses fournisseurs. Cette personne est passionnée par la transformation des défis complexes liés au commerce de détail, au marchandisage et à la chaîne d’approvisionnement en stratégies guidées par les données. Elle s’épanouit dans des environnements où les activités se déroulent à un rythme rapide, elle sait concilier les connaissances techniques avec son sens des affaires et est motivée par le fait que ses modèles alimentent des décisions en matière de vente au détail en contexte réel.

Principales responsabilités

Mettre en application l’intelligence artificielle (IA) générative et la génération à enrichissement contextuel pour permettre l’analyse du langage naturel et les analyses en libre-service pour nos utilisateurs (fournisseurs et négociants).

Élaborer des modèles prédictifs et prescriptifs (p. ex., détection d’anomalies, prévisions, régression, classification).
Élaborer, évaluer et déployer des modèles d’apprentissage automatique dans Vertex AI (Google Cloud Platform) avec des pratiques d’opérations d’apprentissage automatique de qualité production.
Concevoir des pipelines de fonctionnalités robustes dans Airflow et concevoir des produits de données réutilisables pour des analyses et des cas d’usage de l’apprentissage automatique.

Collaborer avec les chefs de produit, les négociants et les fournisseurs pour concevoir des essais (tests A/B, inférence causale) et mesurer les répercussions sur l’entreprise.

Traduire les indicateurs en recommandations claires et exploitables par l’entremise de visualisations, de tableaux de suivi (Looker) et de récits.
Contribuer à l’évolution de la stratégie d’Askuity en matière d’IA en effectuant des recherches et en mettant à l’essai de nouvelles techniques de prévision des séries chronologiques, d’analyses basées sur les grands modèles de langage (modèles LLM) et d’IA agentive.

Compétences

Orientation de la vision et des objectifs.
Gestion de la complexité.
Esprit stratégique.
Stimulation de l’engagement.
Collaboration.

Aptitudes

Excellente maîtrise de Python (pandas, scikit-learn, TensorFlow, PyTorch) et de SQL.
Expérience avec les infrastructures infonuagiques d’IA agentive (de préférence Google Cloud Platform : BigQuery, Vertex AI et Looker).
Solide expérience en modélisation statistique, en apprentissage automatique et en conception expérimentale.
Connaissance de l’IA générative et des grands modèles de langage (modèles LLM) pour l’analyse, y compris l’ingénierie de requêtes, la génération augmentée par récupération et la récupération de données intégrées.
Expérience dans le déploiement des modèles et leur maintenance dans le cadre du cycle de vie complet des opérations d’apprentissage machine.

Supérieur immédiat ou subordonnés

Supérieur immédiat : directeur principal, Science des données.

Exigences relatives aux déplacements

Déplacements limités.
Déplacement au siège social chaque année, sur demande.

Exigences physiques

Position assise pendant des périodes prolongées.
Tâches répétitives.

Conditions de travail

Travail de bureau : ordinateur et caméra pour les réunions.

Exigences de base

Diplôme universitaire de premier cycle dans un domaine connexe.

Expérience professionnelle

Au moins trois ans.

Expérience en direction

s. o.

Accréditations

s. o.

Autres exigences

Expérience relative à la vente au détail, au marchandisage, à la chaîne d’approvisionnement ou à l’analyse des biens de consommation courante.
Excellentes aptitudes pour la communication afin de présenter des analyses complexes à des équipes techniques et non techniques.
Capacité à travailler de façon interfonctionnelle avec les intervenants de l’entreprise afin d’établir des priorités et d’offrir des cas d’usage de grande valeur.
Expérience en gestion de produits.
Contributions à du code source ouvert et recherche en apprentissage automatique appliqué.

The pay range for this position is between $62,200.00 - $70,100.00

Apply About employer

More about this job

Responsibilities

The Data Scientist will design, build, and deploy advanced machine learning solutions, including generative AI and predictive models, to drive data-driven retail decisions. They will also collaborate with cross-functional teams to conduct experiments and translate complex insights into actionable business strategies.

Requirements

Candidates must have at least 3 years of work experience and an undergraduate degree in a quantitative field. Proficiency in Python, SQL, and cloud-native AI frameworks, along with experience in retail or supply chain analytics, is required.

Skills

Python
SQL
Pandas
Scikit-learn
TensorFlow
PyTorch
BigQuery
Vertex AI
Looker
Machine Learning
Statistical Modeling
Generative AI
LLMs
Prompt Engineering
RAG
MLOps

Visa sponsorship

Not detected in the job text

Keywords

Data Scientist
Retail Analytics
Machine Learning
Generative AI
Python
SQL
Vertex AI
BigQuery
Looker
Airflow
MLOps
Predictive Modeling
Prescriptive Modeling
Anomaly Detection
Time Series Forecasting
Agentic AI
RAG
Prompt Engineering
A/B Testing
Causal Inference
Supply Chain
Merchandising
Data Products
Feature Pipelines
Cloud Computing
GCP

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