Data Scientist - Agentic AI

About the Role: We are looking for a Data Scientist - Agentic AI with strong foundations in Statistics, Machine Learning and Data Science, along with hands-on experience in Generative AI and AI agents. You will work on real-world business problems in the CPG and Retail space - including demand forecasting, pricing and promotions, supply chain and inventory, customer/shopper analytics, and category management - involving large datasets, predictive and analytical modelling, Generative AI and Agentic AI. The role involves developing AI-powered solutions and contributing to taking them from experimentation to production. The ideal candidate combines strong Data Science fundamentals with practical experience in LLMs, RAG, AI agents, and Python-based application development. Key Responsibilities: Data Science & Analytics •Apply statistical and machine learning techniques to solve CPG/Retail business problems. •Analyze large and complex retail, sales, and supply-chain datasets to identify trends, patterns and actionable insights. •Develop predictive, forecasting, and analytical models (e.g., demand forecasting, pricing, churn, propensity). •Perform data preparation, feature engineering, model validation, and performance evaluation. •Translate business requirements into analytical approaches and measurable outcomes. Generative AI & Agentic AI •Develop LLM-based applications and AI agents for business use cases. •Build agentic workflows involving tool calling, APIs and business data. •Develop RAG-based solutions using appropriate retrieval and grounding techniques. •Integrate LLMs with databases, APIs, and external tools. •Contribute to multi-agent and agent orchestration solutions. •Develop and execute evaluation approaches to assess AI/agent output quality. Python & Backend: •Develop production-quality Python applications and services. •Build APIs using FastAPI or similar frameworks. •Integrate databases, ML models, LLMs, and external APIs. •Work with SQL and relational databases such as PostgreSQL. •Follow good coding, testing, version-control and software engineering practices. Deployment & Production: •Containerize applications using Docker. •Support deployment of AI applications on AWS, Azure, or GCP. •Work with CI/CD, monitoring, and logging as required. •Collaborate with engineering and platform teams to productionise AI solutions. •Troubleshoot and improve AI applications in production. Collaboration: •Work closely with Senior Data Scientists, Data Engineers, Software Engineers, and business stakeholders. •Contribute to technical design and solution development. •Clearly communicate analytical findings and technical concepts to technical and non-technical stakeholders. Skills & Qualifications Required Skills & Qualifications: • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or related discipline. • 3+ years of experience in Data Science, AI, Machine Learning, GenAI or related areas. • Strong Statistics and Machine Learning fundamentals: predictive modelling, forecasting, model validation. • Strong Python and SQL skills. • Hands-on experience with Generative AI / LLMs. • Practical experience building AI agents or agentic workflows (tool calling, orchestration) - basic chatbot or prompt-engineering experience alone is not sufficient. • Experience developing APIs or backend services (FastAPI or similar). • Working knowledge of PostgreSQL or an equivalent relational database. • Git / version control and standard software engineering practices. • Experience with Docker and at least one cloud platform (AWS, Azure or GCP). • Strong analytical and problem-solving skills. Preferred Skills: • LangGraph, LangChain or equivalent agent/orchestration frameworks. • Vector databases and advanced RAG techniques. • Multi-agent systems design and orchestration. • LLM / agent evaluation methodologies. • Basic CI/CD, monitoring and logging practices. Additional Skills (Nice To Have): • Redis / Celery / Kafka / RabbitMQ. • Kubernetes / AWS ECS / EKS. • MLOps / LLMOps / GenAIOps experience. • Prior experience building AI-powered applications or portals. • Prior experience in CPG or Retail - e.g., demand planning, trade promotion, category management, or shopper/customer analytics. What We Look For: We are looking for a Data Scientist who is strong in Data Science fundamentals and has hands-on exposure to the rapidly evolving world of Generative AI and Agentic AI. Candidates should be able to demonstrate what they have personally built and explain the technical decisions behind their work. Basic chatbot or prompt-engineering experience alone will not be considered sufficient for the Agentic AI requirement. Why Join Us? •Build next-generation Agentic AI solutions for real-world CPG and Retail business problems. •Work across Data Science, Machine Learning, GenAI and AI Engineering. •Work with large and complex business datasets across the retail value chain. •Take AI solutions from experimentation towards production. •High ownership and opportunity to work on emerging AI technologies. •Work closely with experienced Data Scientists, Engineers and business stakeholders.