S&C Global Network - AI - CDI - Data Science Analyst

Accenture in India; Maharashtra; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Accenture in India is seeking an AI Decision Science Analyst in Gurgaon to lead design, development, and deployment of autonomous AI agents and multi-modal solutions that can reason, plan, and act across complex business workflows. You will leverage Generative AI, Agentic AI frameworks, and MCP integrations to deliver intelligent orchestrations and seamless system integrations for diverse industries.

Expect collaboration with cross-functional teams and a consulting environment demanding high

Qualifications

• Minimum 4 years of AI/ML experience with Generative AI and agentic systems.
• Bachelor's or Master's in Statistics, CS, Mathematics, AI/ML, or related fields with excellent academics.

Responsibilities

• Advanced Generative AI & Agentic System Development: design and implement AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures.
• Develop multi-agent systems that can collaborate, negotiate, and execute complex workflows autonomously.
• Implement MCP integrations for seamless communication between AI systems and external tools/APIs.
• Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities.

Skills

Generative AI

Agentic AI Systems

Model Context Protocol (MCP)

Large Language Models (LLMs)

Multi-Agent Systems

Python

SQL

AI Agent Orchestration

Education

Bachelor's or Master's degree in Statistics, Computer Science, Mathematics, AI/ML, or related disciplines

Tools

AI Refinery

LangChain

LlamaIndex

AutoGen

Crew AI

Spark

AWS

Azure

GCP

NLP

Computer Vision

Vector Databases

RAG

Function Calling

Tool Integration

Job description

Job Title – Ind & Func AI Decision Science Consultant - S&C GN

Management Level : 9 - Consultant

Location: Gurgaon

Must have skills:

Generative AI, Agentic AI Systems, Model Context Protocol (MCP), Large Language Models (LLMs), Multi-Agent Systems, Python, SQL, AI Agent Orchestration

Good to have skills:

AI Refinery, LangChain, LlamaIndex, AutoGen, Crew AI, Spark, Cloud Platforms (AWS, Azure, GCP), NLP, Computer Vision, Vector Databases, RAG (Retrieval-Augmented Generation), Function Calling, Tool Integration

Experience:

Minimum 4 years of experience in AI/ML with demonstrated expertise in Generative AI applications and agentic systems, preferably within a consulting environment

Educational Qualification:

Bachelor's or Master's degree (BE/BTech/MBA/MS) in Statistics, Computer Science, Mathematics, AI/ML, or related disciplines with an excellent academic record

Job Summary:

As an AI Decision Science Analyst, you will lead the design, development, and deployment of sophisticated AI agents and multi-modal AI solutions that can autonomously execute complex business workflows. You will leverage cutting-edge Generative AI, Agentic AI frameworks, and Model Context Protocol (MCP) integrations to create intelligent systems that can reason, plan, and act independently to solve complex business challenges across various industries. Your expertise will drive innovation in autonomous AI solutions and deliver transformative value for clients through intelligent agent orchestration and seamless system integrations.

Roles & Responsibilities:

• Advanced Generative AI & Agentic System Development
  • Design and implement sophisticated AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures
  • Develop multi-agent systems that can collaborate, negotiate, and execute complex workflows autonomously
  • Implement Model Context Protocol (MCP) integrations for seamless communication between AI systems and external tools/APIs
  • Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities
• Leverage Advanced Data Science Techniques:
  • Develop solutions using Computer Vision, Machine Learning, and Large Language Models (LLMs).
  • Define data requirements, clean, aggregate, analyze, and interpret data while conducting data quality assessments.
• Develop and Implement AI Models:
  • Build and deploy AI models and Generative AI applications.
  • Train and fine-tune LLMs using large-scale datasets to optimize performance and accuracy.
  • Evaluate model performance and implement iterative improvements.
• Solution Integration and Deployment:
  • Collaborate to integrate AI solutions into end-to-end workflows, ensuring scalability.
  • Utilize cloud platforms like AWS, Azure or GCP for model development and deployment.
• Innovation and Knowledge Sharing:
  • Stay updated on advancements in AI and Data Science, exploring innovative techniques and frameworks.
  • Document methodology and findings for effective knowledge sharing.