Leveraging AI to solve complex business problems in the supply chain and IT space for a leading multinational retailer.
Requirements
- Hands-on experience with Copilot Studio or Azure Data Studio for Data Science and Data Engineering , AI assistant that helps analyze and visualize data
- Strong hands-on expertise with AI tools, libraries, and frameworks.
- Demonstrated experience deploying agentic AI solutions (e.g., AI agents that perform autonomous decision-making or task execution).
- Strong understanding and practical experience with Co-Pilot tools.
- Familiarity with cloud platforms and MLOps practices.
- Experience with large language models (LLMs), retrieval-augmented generation (RAG), or enterprise knowledge management tools.
Responsibilities
- Design, develop, and deploy AI and machine learning models tailored to optimize supply chain processes and decision-making.
- Utilize AI tools and frameworks to build agentic AI systems that can automate and augment complex tasks.
- Implement and manage Co-Pilot-style solutions to assist internal users with intelligent automation and data-driven decision support.
- Translate complex data insights into clear, actionable recommendations through compelling visualizations, presentations, and written reports.
- Work closely with IT stakeholders to ensure smooth integration of data science solutions into existing infrastructure and workflows.
- Stay updated on the latest advancements in AI, machine learning, and supply chain technologies to continuously enhance solution capabilities.
Other
- Collaborate with cross-functional teams within the IT and supply chain domains to understand business challenges and identify opportunities for AI-driven solutions.
- Excellent verbal and written communication skills, with a proven ability to present technical findings to diverse audiences.
- Comfortable working in IT-driven environments, collaborating with engineers, analysts, and business users.
- Experience in Supply Chain operations or technology is preferred but not required.
- Background in retail or logistics data analytics.
