Senior Data Scientist - Agentic AI

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.
• Strong 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.