Data Scientist - NLP/Generative AI (India)

Location : Mumbai / Bangalore (Mumbai Preferred)

Experience : 2 - 3 Years

Key Responsibilities

• Develop and deploy Machine Learning, NLP, and Generative AI solutions for business use cases.
• Design and implement text analytics models to derive insights from large volumes of structured and unstructured data.
• Build and optimize NLP pipelines for classification, information extraction, semantic search, and insight generation.
• Develop Document Intelligence solutions leveraging OCR, Vision AI, and Large Language Models.
• Create end-to-end AI solutions, including model development, deployment, monitoring, and post-production support.
• Collaborate with business stakeholders to understand requirements and translate them into scalable AI products.
• Evaluate and implement emerging AI and GenAI technologies to solve business problems.

Required Skills &

Experience

Machine Learning &

• Data Science :
• Strong foundation in Machine Learning, Statistics, and Applied Data Science.
• Experience delivering ML solutions in production environments.
• Experience handling large-scale datasets (200K records).

NLP &

• Text Analytics :

Hands-on experience in

• Text Classification
• Named Entity Recognition (NER)
• Information Extraction
• Semantic Search
• Topic Modeling
• Text Summarization
• Insight Generation from Unstructured Text

Experience with

• BERT
• Sentence Transformers
• Transformer Architectures
• Embeddings and Vector Representations

Generative AI

• Experience working with Large Language Models (LLMs).
• Understanding of Prompt Engineering and GenAI application development.
• Experience implementing business-focused GenAI use cases.

Vision AI &

• Document Intelligence :

Experience with

• OCR Technologies
• Amazon Textract or equivalent tools
• Vision Language Models (VLMs)
• PDF and Document Information Extraction
• Intelligent Document Processing Solutions

Development &

• Deployment :
• Solid programming skills in Python.
• Experience deploying AI models into production.
• Exposure to APIs, cloud platforms, and MLOps practices.
• Experience supporting and maintaining deployed AI solutions.