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Job Description: AEY GDS – Data and Analytics (D&A) – Senior – Senior Data Scientist
Role Overview
We are seeking an experienced Supply Chain professional (3–7 years) with strong functional expertise and hands-on exposure to AI, Generative AI, LLMs, or digital automation. The role focuses on designing and implementing Agentic AI–driven supply chain solutions, combining domain expertise with modern AI capabilities.
The ideal candidate understands supply chain processes (planning, procurement, inventory, logistics, S&OP) and can work closely with functional teams to translate business needs into autonomous agent workflows. Experience with optimization, NLP/LLMs, and AI solution design will be an added advantage.
Responsibilities
Supply Chain Functional Responsibilities
- Analyze supply chain processes across demand planning, supply planning, procurement, production planning, logistics, and inventory management.
- Translate business challenges into AI/agent-driven use cases, workflows, and decision frameworks.
- Define requirements, KPIs, data needs, and functional specifications for AI-enabled supply chain solutions.
- Validate AI/ML outputs—including forecasts, optimization recommendations, exception insights—and map them to business rules.
Agentic AI & Technical Responsibilities
AI/LLM/GenAI Solutioning
- Contribute to designing autonomous Agentic AI supply chain solutions, including agent roles, reasoning flows, and decision loops.
- Assist in building and validating AI agents using LLMs, RAG, prompt engineering, and domain knowledge modeling.
- Stay updated on latest advancements in LLMs, Generative AI, and agent-based architectures, assessing their applications in supply chain use cases.
Integration & Model Implementation
- Integrate with APIs and libraries such as Azure OpenAI GPT models, Hugging Face Transformers, and other relevant frameworks.
Support implementation and optimization of end-to-end AI pipelines (data model agent- workflow).
- Work with vector databases (e.g., Redis), NoSQL stores, and similarity search for knowledge retrieval and contextual decision-making within agents.
Research & Evaluation
- Evaluate advanced AI techniques (transfer learning, domain adaptation, optimization algorithms) for supply-chain-specific tasks.
- Define evaluation metrics to measure the relevance, accuracy, and business impact of agent recommendations and outputs.
Data Engineering & MLOps Collaboration
- Collaborate on data curation, cleaning, and preprocessing for AI and optimization models in supply chain contexts.
- Support MLOps practices around versioning, deployment, monitoring, and scaling of AI/LLM models.
- Contribute to CI/CD pipeline execution and use tools like Docker, Kubernetes, and Git for AI model deployment.
Client & Stakeholder Collaboration
- Work closely with business stakeholders, supply chain SMEs, and technical teams to understand requirements and deliver tailored AI solutions.
- Participate in workshops, solution demos, PoV/PoC delivery, and client presentations.
- Communicate complex analytical insights and AI-driven decisions in clear business language.
Requirements
Education
- Bachelor’s or Master’s degree in Supply Chain, Engineering, Operations, Computer Science, or related fields.
- APICS / CPIM / CSCP certifications are a plus.
Experience
- 3–7years of experience in supply domain Analytics
- Exposure to AI/ML, GenAI, LLMs, or digital supply chain transformation initiatives.
- Experience with Simulation/Optimization in supply chain would be preferred
Technical Skills
- Understanding of machine learning, NLP, or LLM-based techniques (GPT, Transformer models, BERT, etc.).
- Familiarity with optimization (MIP, linear programming) is preferred.
- Good exposure to cloud platforms (Azure, AWS, GCP).
- Ability to annotate requirements, work with APIs, vector databases, and integrate supply chain workflows with AI agents.
Soft Skills
- Strong analytical and problem-solving ability.
- Excellent communication and stakeholder management.
- Ability to work in agile, cross-functional teams.
- Passion for innovation and staying updated with emerging AI technologies.
Good-to-Have Skills (Bonus)
- Hands-on knowledge of optimization tools (Gurobi, CPLEX, Pyomo).
- Experience with DevOps/MLOps: CI/CD, IaC (Terraform), monitoring & logging frameworks.
- Exposure to trusted AI practices (fairness, transparency, explainability).
- Work experience in consulting or global delivery environments.
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