Data Science Manager
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
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 Fusion
- Define the roadmap and strategy to enhance predictive analytics, machine learning, GenAI 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 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 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
- Measure and evaluate AI and GenAI solutions using business, technical, and model quality metrics while continuously optimizing performance
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 Kernal, OpenAI APIs, or equivalent GenAI platforms
- Cloud-based data platforms (GCP, AWS, Azure) and big data technologies
- Statistical modelling and machine learning
- Data management & engineering awareness
- Programming and MLOps practices
More about this job
Responsibilities
Lead and mentor a data science team developing AI-enabled capabilities for Fusion, including predictive analytics, machine learning, generative AI, intelligent automation, and decision support. Partner with product, design, and engineering teams to integrate and evaluate AI solutions, maintain data quality and security, and improve supplier insights and performance.
Requirements
The role calls for experience with Python, R, SQL, statistical modeling, machine learning frameworks, and cloud-based data platforms. It also requires expertise in generative AI techniques and tools, including LLMs, prompt engineering, retrieval-augmented generation, embeddings, vector databases, model evaluation, and MLOps practices.
Skills
- Python
- R
- SQL
- Machine Learning
- TensorFlow
- PyTorch
- Generative AI
- Large Language Models
- Prompt Engineering
- Retrieval-Augmented Generation
- Natural Language Processing
- LangChain
- Cloud Data Platforms
- Statistical Modeling
- MLOps
- Data Management
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Management & Leadership
- Software
- Retail
Keywords
- Data Science
- Artificial Intelligence
- Generative AI
- Fusion
- Business Intelligence
- Supplier Analytics
- Predictive Analytics
- Machine Learning
- Natural Language Processing
- Large Language Models
- Retrieval-Augmented Generation
- Prompt Engineering
- Embeddings
- Vector Databases
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- OpenAI APIs
- TensorFlow
- PyTorch
- Python
- R
- SQL
- GCP
- AWS
- Azure
- Big Data
- MLOps
- Responsible AI