Senior Data Scientist

Company :

Mahindra & Mahindra Ltd About the Team Mahindra AI Division is the AI innovation arm within Mahindra Group. The division experiments with state-of-the-art AI technologies and is focused on developing and delivering cutting-edge AI products to the group. With the division’s team-expansion plan, there is an excellent opportunity for your career growth in the team.Responsibilities Provide data science and AI expertise to design, build, and deliver scalable ML and deep learning solutions. Work extensively with tabular data to develop predictive models, perform feature engineering, and optimize performance for real-world applications. Apply conventional machine learning techniques (e.g., regression, classification, ensemble methods) alongside advanced deep learning methods. Build and optimize deep learning models for structured and unstructured data, including text and audio. Lead development of solutions for audio data, including classification, recognition, and signal processing tasks. Design, fine-tune, and deploy LLMs (Large Language Models), SLMs (Small Language Models), and other Generative AI solutions for diverse business applications. Translate business problems into well-structured ML / AI problems and deliver actionable insights. Deploy production-grade models with a focus on efficiency, scalability, and maintainability. Collaborate with cross-functional teams including product managers, engineers, and domain experts to deliver high-impact projects. Mentor junior data scientists and interns, fostering innovation and best practices. Qualification Requirements : Educational : Bachelor’s degree with at least 7 years of experience or Master’s with at least 4 years of experience in Data Science / ML / AI. Preferred to have degree from a Tier-1 / 2 institute (IIT / IISc / NITs if studied in India) or a globally top-ranked university (as per QS). Technical : Proven expertise working with large-scale tabular data and building machine learning models. Strong knowledge of conventional ML algorithms (tree-based models, SVMs, clustering, etc.). Hands-on experience with deep learning frameworks such as TensorFlow / PyTorch. Mandatory expertise in LLMs, SLMs, and Generative AI, including fine-tuning, prompt engineering, and deployment. Proficiency in Python and libraries such as scikit-learn, pandas, NumPy. Exposure to model deployment frameworks and tools (ONNX, Triton, TensorRT, FastAPI, etc.). Familiarity with cloud platforms (Azure / GCP) for training and deploying ML solutions. Experience with Databricks is a plus. Strong understanding of MLOps practices, reproducibility, and model monitoring. Other : Excellent written and verbal communication skills in English. Demonstrated experience working collaboratively in cross-functional teams. Ability to balance research and production priorities while meeting deadlines. Passionate about applying AI / ML to solve diverse real-world problems, especially at the intersection of GenAI and enterprise AI adoption.