Data Scientist

About the Role

We are looking for a Data Scientist with 3-6 years of experience in developing Natural Language Processing (NLP) and Generative AI (GenAI) solutions. The ideal candidate is hands-on with a proven track record of designing and developing agentic AI solutions within customer-facing roles. You will be responsible for researching and building state-of-the-art AI solutions that can perform multi-step reasoning to solve complex business challenges. Experience with Databricks (especially MLOps Stacks) is highly desirable.

Key Responsibilities

• Translate business challenges into solvable AI use cases, such as document understanding, web search, automated Q&A, summarisation, and workflow automation.
• Stay updated with the latest GenAI/LLM advancements and evaluate them for feasibility and potential use.
• Design, build, and deploy LLM-powered retrieval-augmented generation (RAG) pipelines and agentic AI solutions, including multi-step reasoning systems, tool-using agents, and associated pipelines.
• Build basic UI frontends (e.g., using Streamlit, Flask) for internal demos or client-facing pilot GenAI applications.
• Apply MLOps best practices, including MLflow-based tracking, Docker containerization, and CI/CD for GenAI pipelines.
• Develop customer demos and prototypes using Databricks Mosaic AI suite.
• Contribute to both internal R&D efforts and customer implementations, including rapid POCs and scalable production deployments.

Required Qualifications

• 3-6 years of implementation experience in data science, with a strong focus on NLP and agentic AI applications in a customer-facing role.
• Must have productionized machine learning or deep learning models.
• Familiarity with SQL and working with large, complex datasets.
• Proficiency in Python and NLP / LLM libraries/tools such as HuggingFace Transformers, LangChain, LangGraph, etc.
• Practical experience with prompt engineering, chunking, vector embeddings, semantic search, RAG pipelines, and LLM fine-tuning.
• Understanding of GenAI-specific challenges: hallucination, prompt security, rate limits, cost optimisation, etc.
• Strong foundation in statistics, including:
  • Model assumptions and diagnostics
  • Evaluation metrics and error analysis
  • Probabilistic modelling, hypothesis testing, and uncertainty quantification
  • Feature importance and interpretability techniques
• Experience in MLOps tools and processes, including:
  • Model versioning and experiment tracking (e.g., MLflow)
  • Containerization (Docker)
  • CI/CD for ML workflows (e.g., GitHub Actions, Azure DevOps, or similar)
  • Model monitoring and retraining workflows
• Desirable: Hands-on experience with Databricks for mode development and deployment.
• Desirable: MLOps experience on Databricks.
• Required: Experience with at least one cloud provider and the native AI/ML-related tools/services (Azure, AWS, or GCP).
• Required: Strong analytical and communication skills, with a demonstrated ability to convert business requirements into AI solutions.
• Required: Excellent English communication skills (written and verbal) are mandatory, as this role supports multiple international markets.

Educational Background

• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, Operational Research, or a related quantitative discipline.
• Relevant certifications (e.g., Databricks / AWS / Azure /GCP AI/ML certifications) are a plus.

Workplace Flexibility

This is a WORK FROM OFFICE 5 DAYS A WEEK - COIMBATORE.