DATA SCIENTIST

About The Role We are looking for a curious and motivated analyst/engineer to join our Data & AI team. You will work on real-world data pipelines, build and evaluate ML models, and deploy intelligent agentic workflows powered by modern LLM tooling. This is a hands-on, fast-paced role. Roles and responsibilities Effective knowledge sharing to researchers, coupled with Gen AI technology upgrading and mentoring Collect, clean, and transform structured/unstructured data for analysis and model training. Build and fine-tune ML models (classification, regression, clustering, NLP) using Python. Develop and test agentic AI workflows using LLM APIs (Claude, GPT-4o, Gemini) with tool use, memory, and planning. Integrate agents with external tools — search, databases, APIs — using MCP or function calling. Create PowerBi dashboards, visualisations, and reports to communicate insights to stakeholders. Evaluate and benchmark LLM outputs; implement prompt engineering and RAG pipelines. Assist in deploying models and agentic applications to Azure cloud or on-premise environments. Collaborate with cross-functional teams to understand business requirements and deliver AI-driven solutions. Educational Qualification M.E/M.Tech : Multi-disciplinary Engg. domain with Data Science, Artificial Intelligence, Statistics, or a related field. Relevant certifications (Azure : Data Analytics, ML Specialty, DeepLearning.AI, etc.) are a strong plus. A GitHub portfolio demonstrating hands-on projects is strongly preferred over certifications alone. Nice to Have Experience building end-to-end agentic applications [ReAct agent, multi-agent system using CrewAI or AutoGen] Familiarity with MCP server development or custom tool integrations for LLMs. Contributions to open-source AI/ML projects on GitHub. Knowledge of LLM evaluation frameworks such as RAG Exposure to MLOps practices: experiment tracking, model versioning, and CI/CD pipelines. Soft skills Strong analytical thinking and problem-solving ability. Eagerness to learn rapidly evolving AI/ML technologies and frameworks. Clear written and verbal communication for presenting findings to non-technical stakeholders. Ability to work independently and collaboratively in an agile team environment. Intellectual curiosity and a builder's mindset — you like shipping things, not just experimenting.