S&C Global Network - AI - Hi Tech - Data Science Analyst 2

Accenture in India; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Accenture in India is seeking a Data Science Analyst to lead innovative projects across Consumer Tech, Enterprise Tech, and Semiconductors, combining hands-on technical work with client delivery oversight.

You will develop GenAI solutions, build scalable data pipelines, and apply Python/SQL and ML frameworks to create predictive models and optimization tools for diverse business needs in India.

Qualifications

• Hands-on experience applying GenAI to NLP, CV, and multimodal use cases.
• Experience building AI-powered analytics and decision-support systems.
• Familiarity with vector DBs, model deployment, and monitoring.

Responsibilities

• Develop fine‑tune models for NLP, Computer Vision, and multimodal applications.
• Build autonomous workflows using prompt engineering, API/tool integration, and orchestration frameworks (LangChain, LlamaIndex, AutoGen).
• Monitor, debug, and fine‑tune AI agents to improve context handling, error recovery, and response quality.
• Build retrieval pipelines using vector databases such as Pinecone, FAISS, Weaviate or Milvus

Skills

Generative AI

Prompt engineering

API integration

Orchestration frameworks

Model fine-tuning

Vector databases

Python

SQL

TensorFlow

PyTorch

Tools

LangChain

LlamaIndex

AutoGen

Pinecone

FAISS

Weaviate

Milvus

SageMaker

Azure Machine Learning

AWS

Job description

Job Summary

We are seeking a highly skilled and motivated Data Science 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

• Develop fine‑tune models for NLP, Computer Vision, and multimodal applications, leveraging GenAI frameworks.
• Build autonomous workflows using prompt engineering, API/tool integration, and orchestration frameworks (LangChain, LlamaIndex, AutoGen)
• Monitor, debug, and fine‑tune AI agents to improve context handling, error recovery, and response quality.
• Build retrieval pipelines using vector databases such as Pinecone, FAISS, Weaviate or Milvus

Cloud Platform Expertise

• Implement scalable data science workflows on Azure or AWS for marketing, supply chain, or sales analytics projects.
• Leverage cloud‑native tools for model training, deployment, and monitoring (e.g., SageMaker, Azure Machine Learning).

Data Science and Engineering

• Perform advanced analytics using Python, SQL, and machine learning frameworks like TensorFlow or PyTorch.
• Develop predictive models, recommendation systems, and optimization solutions tailored to business needs.
• Manage large‑scale datasets, preprocessing pipelines, and feature engineering for diverse data modalities.