Sr. Expert - Data Science

Role & responsibilities

Visionary AI leader to spearhead enterprise-wide Artificial Intelligence across Mahindra Group Companies. As the Senior Expert Data Science/AI, you will be responsible for defining strategy, architecting scalable platforms, and delivering intelligent solutions powered by Machine Learning (ML), Generative AI, and Data-driven systems.

•    Define and execute enterprise-wide AI and automation strategy.
•    Architect and deliver AI platforms leveraging LLMs, SLMs, RAG, and vector databases.
•    Lead end-to-end AI lifecycle: research, prototyping, PoC, and enterprise deployment.
•    Build and optimize scalable data pipelines,Models, APIs, and automation workflows on cloud platforms.
•    Drive adoption of GenAI frameworks such as LangChain, LlamaIndex, Hugging Face, and OpenAI APIs.
•    Ensure adherence to responsible AI practices, governance, and ethics.
•    Mentor, grow, and lead high-performing AI/Automation teams across the organization.

Experience

12+ years

Qualifications

BE/ME/PHD

Functional skills required to execute the role

•    AI/ML Expertise: Hands-on with ML models, Deep Learning, Generative AI, and Multimodal AI.
•    Frameworks & Tools: LangChain, LlamaIndex, Hugging Face, PyTorch, TensorFlow, OpenAI APIs, Vector DBs (FAISS, Pinecone, OpenSearch).
•    Data & Architecture: Strong expertise in data engineering, API design, and cloud-native architectures.
•    Cloud Platforms: AWS, GCP, Azure (BigQuery,Glue,EMR,SageMaker, Vertex AI, Azure ML,s3,Dataflow etc).
•    Leadership: Proven record in leading AI initiatives, scaling teams, and aligning AI to business outcomes.
•    ML Models: Proficiency in Regression, Classification (Tree-based, XGBoost, LightGBM, CatBoost), Clustering (K-Means, DBSCAN), Dimensionality Reduction (PCA, UMAP), CNNs (vision), RNNs/LSTMs & Transformers (NLP & time-series), Forecasting (ARIMA, Prophet, DeepAR).
•    Programming & Databases: Expert in Python, SQL and knowledge of SQL/NoSQL databases(PostgreSQL,MongoDB,mySQL,ES,Redshift).
•    MLOps & DevOps: Experience with Docker, Kubernetes, GitHub, AutoML, and ML pipelines.
•    Knowledge of open source tools and technology 

Good to Have
•    Experience working with Manufacturing AI use cases (e.g., predictive maintenance, computer vision, quality control, supply chain optimization).
•    Knowledge of Chatbot development, conversational AI, or enterprise chatbot frameworks.

Behavioural Competencies required

• Analytical Thinking & Problem-Solving
• Adaptability & Continuous Learning
• Collaboration & Teamwork
• Innovation & Experimentation
• Accountability & Ownership