We are looking for a Senior Data Scientist – Agentic AI to lead the design and development of advanced Data Science, Generative AI and Agentic AI solutions for 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.

This role requires strong expertise in Statistics, Machine Learning and Data Science, combined with hands-on experience designing LLM-based applications, AI agents and agentic workflows, and taking AI solutions into production.

The Senior Data Scientist will own problems end-to-end — from understanding the business requirements and designing the solution architecture to development, evaluation, deployment and productionisation.

The ideal candidate is both a strong Data Scientist and a hands-on AI builder, with the ability to make sound technical decisions and guide other team members.

Key Responsibilities

Data Science & Advanced Analytics

•Lead the application of Statistics, Machine Learning, forecasting, prediction and optimization techniques to complex CPG/ Retail business problems.

•Design analytical approaches for large and complex datasets.

•Develop, validate, and optimize machine learning and forecasting models.

•Identify appropriate modelling approaches based on business objectives and data characteristics.

•Establish robust model validation and performance measurement frameworks.

•Translate complex analytical findings into actionable business recommendations.

Agentic AI & Generative AI:

•Design and develop production-grade AI agents and multi-agent systems.

•Define agent architecture, orchestration, tool usage and workflow design.

•Build LLM-based analytical workflows that can reason over business data and interact with tools, APIs and business systems.

•Design RAG solutions and retrieval strategies appropriate to the use case.

•Develop approaches for agent memory, state management and workflow execution.

•Design evaluation frameworks to measure accuracy, reliability, groundedness and quality of AI/agent outputs.

•Identify and address hallucination, reliability, and failure-mode issues in AI applications.

•Stay current with emerging Agentic AI and GenAI technologies and assess their practical application.

Solution Architecture & Engineering:

- Design end-to-end AI solution architectures covering Data Science, LLMs, agents, APIs,



databases and deployment.
- Develop backend services using Python, FastAPI or equivalent frameworks.
- Integrate databases, ML models, LLMs, APIs and external tools.
- Review code and technical implementations for quality, scalability, and maintainability.
- Establish engineering and development best practices for AI solutions.

Cloud & Production:
- Lead containerization and deployment of AI applications using Docker.
- Deploy and operate AI services on AWS, Azure or GCP.
- Contribute to CI/CD, monitoring, logging and production reliability.
- Work with Platform/DevOps teams on scalable AI application architecture.
- Diagnose production issues and drive improvements in system reliability and performance.

Technical Leadership

- Own AI solutions from problem definition through production.
- Break complex problems into executable technical components.
- Mentor Data Scientists and junior team members.
- Review technical approaches and provide guidance on modelling and AI architecture.
- Collaborate with Data Engineering, Software Engineering and Platform/DevOps teams.
- Work directly with business stakeholders and clients when required.
- Contribute to technical standards, reusable components and AI best practices within the organization.

Skills & Qualifications

Required Skills & Qualifications

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related discipline.
- 5+ years of experience in Data Science, AI, Machine Learning, GenAI or related areas.
- Strong Statistics and Machine Learning fundamentals: forecasting, prediction, optimization, model validation, largescale data analysis.
- Robust Python and SQL skills.
- Significant hands-on experience with Generative AI / LLMs (RAG, embeddings, prompt engineering, LLM evaluation).
- Demonstrated experience designing and building AI agents or agentic workflows -including agent orchestration, tool calling, agent memory/state, and agent evaluation. Experience limited to prompt engineering,



basic LLM API integrations or simple chatbot development is not sufficient.
- Experience taking AI/ML solutions into production.
- Experience developing APIs or backend services (FastAPI or similar).
- Working knowledge of PostgreSQL or an equivalent relational database, and Git/version control.
- Hands-on experience with Docker and at least one cloud platform (AWS, Azure or GCP).
- Strong problem-solving and analytical ability, with the ability to independently own technical problems and drive them to completion.

Preferred Skills

- LangGraph, LangChain or equivalent agent orchestration frameworks.
- Advanced RAG architectures and vector databases.
- Multi-agent systems design.
- Guardrails and reliability engineering for LLM/agent outputs.
- CI/CD, monitoring and logging for production AI systems.
- Client-facing experience and experience mentoring Data Scientists or AI Engineers.

Additional Skills (Nice to Have):
- Kubernetes / AWS ECS / EKS.
- Redis / Kafka / RabbitMQ / Celery.
- Terraform.
- MLOps / LLMOps / GenAIOps experience.
- Experience building enterprise AI 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 hands-on Senior Data Scientist, not someone who is purely a AI architect.

The ideal candidate can move from understanding the business problem, to designing the Data Science/AI approach, to building the solution, evaluating it, deploying it, and improving it in production.

Candidates should be able to demonstrate significant personal contribution to the AI/ML systems they have built.

Experience limited to prompt engineering, basic LLM API integrations or simple chatbot development will not be sufficient.

Why Join Us?

- Lead the development of next-generation Agentic AI solutions for real-world CPG, and Retail business problems.
- Solve complex business problems using Data Science and AI.
- Work across Data Science, ML, GenAI, Agentic AI and AI Engineering.
- Own solutions end-to-end from concept to production.
- Influence the architecture and evolution of Aria's AI capabilities.
- Work with enterprise clients and complex business datasets across the retail value chain.
- Mentor and collaborate with a growing AI team.
- High ownership and opportunity to work with rapidly evolving AI technologies.

📌 Senior Data Scientist - Agentic AI (Delhi)
🏢 Aria Intelligent Solutions
📍 Delhi