S&C Global Network - AI - Hi Tech - Data Science Sr. Analyst

Accenture in India; Bengaluru; On-site; INR 2,800,000 - 4,800,000; Full time

Job summary

Accenture in India is seeking a Data Science Sr. Analyst to lead innovative GenAI and analytics projects across Consumer Tech, Enterprise Tech, and Semiconductors.

The role blends hands-on technical work with client delivery management in cloud-based analytics. You will design, fine-tune GenAI models, build scalable AI pipelines on Azure or AWS, and develop predictive and optimization solutions with robust data engineering.

Qualifications

• Experience with GenAI, NLP, CV, or multimodal AI
• Hands-on data science delivery with client-facing projects
• Familiarity with cloud-based analytics and MLOps practices

Responsibilities

• Design and fine-tune GenAI models for NLP, CV, and multimodal use cases.
• Architect agentic AI solutions with orchestration frameworks and APIs.
• Optimize agent workflows with RAG pipelines and context handling.
• Build scalable retrieval pipelines using vector databases for enterprise integration.
• Design scalable AI/ML workflows on Azure or AWS with cost/performance focus.
• Leverage cloud-native MLOps tools for model training, deployment, monitoring, and governance.
• Develop advanced predictive models and data pipelines for GenAI/ML workloads.

Skills

GenAI

NLP

Computer Vision

Multimodal AI

Cloud platforms

MLOps

Job description

Job Summary

We are seeking a highly skilled and motivated Data Science Sr. Analyst to lead innovative projects and drive impactful solutions in domains such as Consumer Tech, Enterprise Tech, and Semiconductors. This role combines hands-on technical expertise, and client delivery management to execute cutting-edge projects in Generative AI, decision science, and cloud-based analytics.

Key Responsibilities

Generative AI Expertise

• Design and fine-tune GenAI models for NLP, CV, and multimodal use cases, ensuring enterprise scalability.


• Architect agentic AI solutions with orchestration frameworks (LangChain, LlamaIndex, AutoGen), integrating APIs and enterprise knowledge bases.


• Optimize agent workflows by defining monitoring, fine-tuning RAG pipelines, and improving context handling and reliability.


• Build scalable retrieval pipelines using vector databases (Pinecone, FAISS, Weaviate, Milvus) for high-performance enterprise integration.

Cloud Platform Expertise

• Design scalable AI/ML workflows on Azure or AWS for cross-functional domains with cost and performance optimization.


• Leverage cloud-native MLOps tools (SageMaker, Azure ML) for model training, deployment, monitoring, and governance.

Data Science and Engineering

• Develop advanced predictive models, recommendation engines, and optimization solutions, ensuring business relevance and measurable impact.


• Engineer robust data pipelines and feature stores to support GenAI and ML models across structured, unstructured, and multimodal datasets.