Data Scientist
Company Name
Job Description
- Build and deploy Generative AI models using large language models (LLMs) like GPT,Gemini ,Claude, LLaMA, etc.
- Design and develop Retrieval-Augmented Generation (RAG) pipelines for enterprise search and summarization.
- Perform exploratory data analysis, feature engineering, and apply statistical methods to derive insights.
- Work with vector databases (e.g., FAISS, Pinecone, Chroma) and embedding models for semantic search.
- Develop and fine-tune prompts for prompt engineering, few-shot learning, and function calling.
- Collaborate with product and engineering teams to design AI-driven features and solutions.
- Conduct A/B testing, build dashboards, and contribute to ML pipelines in production.
- Stay updated with GenAI research and open-source tools; evaluate new models and frameworks.
- solving high-impact problems involving structured and unstructured data using a wide range of ML/DL techniques.
- The ideal candidate is hands-on, self-driven, and passionate about turning data into intelligent systems.
Job Details
Experience :
4 To 9
Number Of
Vacancies :
1
Job Type :
Permanent
Industry Type : IT/Software
Salary
:
9 Lac - 10 Lac
P.A
Education Summary
UG :
BE/B.Tech
PG :
Any PG Degree
Contact Details
Contact
Person :
NA
Contact
Number :
8030835000
e-mailId :
hr.helpdeskexit@genpact.com
Address :
RMZ One Paramount Porur Chennai, Campus-10,6th Floor, RMZ-One Paramount, Mount Poonamallee High Road, Porur, Chennai- 600116
Office Location
Central Jakarta No 1234, Jakarta, IndonesiaPYTHON AI ML
Experience -
3 to 5
Key Skills -
Python,
Flask,
Django,
FastAPI,
Core Python,
Iterators,
Generators,
OOP Concepts,
Python REPL,
Exception Handling,
Data Structures,
Object Relational Mapper (ORM),
AI Search,
Vector Database,
Relational Data Processing,
Unstructured Data Processing,
Azure App Services,
Cloud Deployment,
AI Application Development,
Machine Learning Integration,
API Development.,
Automation Lead Global Supply Chain Finance
Experience -
8 to 9
ML Engineer
Experience -
8 to 13
Data Scientist
Experience -
4 to 9