Data Scientist – LLM, NLP, ML & Anomaly Detection

Job Title: Data Scientist – LLM, NLP, ML & Anomaly Detection

Location: Pune

Experience Level: 4-8 years

We are looking for a Data Scientist with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), Machine Learning, and Anomaly Detection to join our AI & Data Science team.

Key Responsibilities

• Design, build, and deploy end-to-end AI/ML solutions.
• Develop NLP applications including:
• Named Entity Recognition (NER)
• Text Classification & Sentiment Analysis
• Information Extraction
• Document Summarization & Question Answering
• Semantic Search & Document Similarity
• Build and fine-tune models using Hugging Face Transformers (BERT, RoBERTa, T5, etc.).
• Process unstructured data from PDFs, emails, OCR documents, and web content.
• Develop LLM-based applications using OpenAI, Azure OpenAI, LangChain, and LlamaIndex.
• Design anomaly detection solutions for fraud detection, operational monitoring, and document/text analytics.
• Implement Statistical, ML-based, Deep Learning, and Time-Series anomaly detection techniques.
• Build scalable real-time and batch ML pipelines.
• Perform feature engineering, model training, hyperparameter tuning, and model evaluation.
• Deploy models using FastAPI/Flask and monitor production performance.
• Collaborate with engineering, product, and business teams to deliver AI solutions.
• Create data visualizations and communicate insights to stakeholders.

Required Skills

• 4–8 years of experience in Data Science or Machine Learning.
• Strong Python skills (Pandas, NumPy, Scikit-learn, SciPy).
• Experience with LangChain, LlamaIndex, OpenAI, or Azure OpenAI.
• Hands-on experience with Hugging Face, spaCy, and NLTK.
• Expertise in ML and Deep Learning using PyTorch or TensorFlow.
• Experience with anomaly detection techniques such as Isolation Forest, LOF, One-Class SVM, Autoencoders, and LSTM.
• Knowledge of Time-Series Analysis (ARIMA, Prophet, LSTM).
• Proficiency in SQL and Vector Databases (FAISS, Pinecone, Chroma, Weaviate).
• Experience with AWS, Azure, or GCP.
• Knowledge of Git, Docker, CI/CD, and REST API development.
• Experience with Pydantic for structured outputs and data validation.

Preferred Skills

• OCR and document processing tools (Tesseract, Google Vision API, PyMuPDF).
• MLOps tools such as MLflow, Kubeflow, or Weights & Biases.
• Kafka, Spark Streaming, Kubernetes, Apache Spark, or Dask.
• Experience in Financial Services, Fraud Detection, Risk Management, or Compliance.
• Open-source contributions or AI/ML research publications.

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.