Job Title: Data Scientist
Skills: Artificial intelligence, Machine Learning, NLP, Gen AI, Python, Rest API, Agentic AI, LLM, RAG, Devops and AWS
Experience: 4+ years
Location: Pune and Hyderabad
Duration: Full time

We at Coforge are hiring for Data Scientist role with following skill sets:
LLM & Generative AI
Design, build, and deploy LLM-powered applications using frameworks such as LangChain, LlamaIndex, or OpenAI API.
Develop and optimize prompt engineering strategies (few-shot, chain-of-thought, RAG) to improve the accuracy, consistency, and reliability of LLM outputs.
Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., FAISS, Pinecone, Chroma, Weaviate).
Fine-tune pre-trained LLMs (e.g., GPT, LLaMA, Mistral, Falcon, Claude,Gemini) on domain-specific datasets.
Validate and structure LLM outputs using Pydantic models and output parsers to ensure data integrity.
Natural Language Processing (NLP)
Build end-to-end NLP pipelines for real-world tasks including:
Named Entity Recognition (NER)
Text Classification & Sentiment Analysis




Information & Data Extraction from Documents
Document Summarization & Question Answering
Semantic Search & Document Similarity
Work with the Hugging Face Transformers ecosystem to leverage and fine-tune pre-trained models (BERT, RoBERTa, T5, etc.).
Process large-scale unstructured text data from various sources such as PDFs, emails, scanned documents (OCR), and web content.
Anomaly Detection
Design and implement anomaly detection systems for various domains, including:
Financial fraud detection (unusual transactions, payment anomalies).
Operational anomalies (system logs, network traffic, sensor data).
Text-based anomalies (unusual document patterns, suspicious NLP signals).
Apply a wide range of anomaly detection techniques including:
Statistical Methods: Z-score, IQR, CUSUM.
ML-based Methods: Isolation Forest, One-Class SVM, Local Outlier Factor (LOF).
Deep Learning Methods: Autoencoders, LSTM-based seq

📌 Data Scientist (India)
🏢 Coforge
📍 India