Data Science Manager

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 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 GenAI for FusionDefine the roadmap and strategy to enhance predictive analytics, machine learning, GenAI capabilities, intelligent automation, and decision support functionalitiesCollaborate with leaders from product management, design, and engineering to integrate advanced analytics into the BI toolDesign an implement machine learning models, NLP, LLM-powered applications, retrieval-augmented generation (RAG), prompt engineering, and other AI techniques to improve user experience and insights generationEnsure data integrity, quality, and security across all analytics processesDrive innovation by evaluating emerging AI technologies including foundation models, GenAI frameworks, agentic AI, and responsible AI practicesMeasure and evaluate AI and GenAI solutions using business, technical, and model quality metrics while continuously optimizing performanceSkills:
Python, R, SQL, and machine learning frameworks such as TensorFlow or PyTorchGenAi applications using Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and model evaluation techniquesAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernal, OpenAI APIs, or equivalent GenAI platformsCloud-based data platforms (GCP, AWS, Azure) and big data technologiesStatistical modelling and machine learning
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