Échelle salariale : $160,000 - $190,000

Chez Home Depot Canada, nous voulons que vous vous sentiez valorisé et soutenu. L’échelle salariale indiquée représente uniquement le salaire de base. Votre rémunération globale peut également comprendre des primes semestrielles liées au rendement de l’entreprise, un programme de participation différée aux bénéfices pour vous aider à épargner en vue de la retraite, des avantages sociaux complets, un rabais de 15 % sur l’achat d’actions de Home Depot ainsi que des augmentations salariales fondées sur le mérite. Nous nous engageons à reconnaître vos efforts et à soutenir votre développement au sein de notre entreprise.

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.

Position Overview:

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 Manager, Data Science you will lead the development and integration of AI-enabled capabilities within Fusion, The Home Depot’s Business Intelligence (BI) tool for suppliers. In this role, you will lead a team of data scientists and collaborate with cross-functional stakeholders to enhance decision-making and analytical capabilities within the platform. Your work will be instrumental in optimizing supplier performance, driving insights, and ensuring Home Depot suppliers can leverage data-driven strategies effectively.                                                                                                       

           

Key Responsibilities:                                                                                        

• Lead and mentor a team of data scientists in developing AI-powered solutions, including Generative AI (GenAI), for Fusion.
• Define the AI roadmap and strategy to enhance predictive analytics, machine learning, Gen AI capabilities, intelligent automation, and decision support functionalities.
• Collaborate with leaders from product management, design and engineering to integrate advanced analytics into the BI tool.
• Design and implement machine learning models, NLP, LLM-powered applications, retrieval-augmented generation (RAG), prompt engineering, and other AI techniques to improve user experience and insights generation.
• Ensure data integrity, quality, and security across all analytics processes.
• Drive innovation by evaluating emerging AI technologies including foundation models, GenAI frameworks, agentic AI, and responsible AI practices.
• Communicate findings and AI-driven solutions to senior leadership and stakeholders in a clear and impactful manner.
• Measure and evaluate AI and GenAI solutions using business, technical, and model quality metrics while continuously optimizing performance.

Competencies:                                                                                                             

• Business acumen
• Product thinking
• Data storytelling
• Problem-solving, analytical thinking
• Strategic planning
• Team leadership
• Cross-functional collaboration
• Talent development
• Influencing skills and stakeholder management
• Executive communication                                             

Skills:                                                                                                              

• Python, R, SQL, and machine learning frameworks such as TensorFlow or PyTorch
• GenAI applications using Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and model evaluation techniques
• AI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI APIs, or equivalent enterprise GenAI platforms
• Cloud-based data platforms (AWS, GCP, Azure) and big data technologies
• Statistical modeling and machine learning
• Data management & engineering awareness
• Programming and MLOps practices

                                                                                                     

Direct Manager:                                                                                                                       

• Reports to Director, Product Management

                                                                                                           

                                                                       

Physical Requirements:                                                                                                            

• None

                                   

Hybrid Work:                                                                                                               

• 3 days per week in our downtown Toronto office
• (King / Spadina)                                                                                                      

Working Conditions:                                                                                                                

• Office

                                                                                                                       

Minimum Education:                                                                                                               

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. Ph.D. preferred.

                                                                                   

Minimum Years of Work Experience:                                                                                        

• 5+ years of experience in Data Science, Machine Learning, AI, or GenAI application development, with at least 2 years leading technical teams.

                                                                                   

Minimum Leadership Experience:

• 2 years                                                            

Certifications:                                                                                                              

• None