Senior Manager

Introduction to the Role We are seeking a highly skilled and passionate Data Scientist to join our Supply Chain Operations team You will leverage advanced analytical techniques machine learning and statistical modeling to optimize complex supply chain processes improve operational efficiency and drive data-driven decision-making across our manufacturing and logistics networks This role will help Tata Motors achieve its strategic priorities in enhancing our resilience reducing costs and accelerating product flow in a rapidly evolving automotive landscape Job roles responsibilities Roles responsibilities Design Develop and operationalize AI ML models for key supply chain S OP use cases like Inventory optimization demand forecasting network optimization inventory aging optimization lead time prediction and risk detection Utilize advanced statistical methods machine learning algorithms e g regression classification clustering time series analysis reinforcement learning and operations research techniques e g optimization simulation Conduct in-depth exploratory data analysis to identify trends anomalies and opportunities for improvement within supply chain and operational data Identify critical pain points and inefficiencies in existing supply chain and manufacturing processes and propose data-driven solutions Develop and implement strategies for cost reduction lead time optimization waste reduction and quality improvement across the supply chain Contribute to supply chain network design and capacity planning initiatives using data-driven insights Drive the adoption of data science solutions by working collaboratively with operational teams for successful implementation and change management Develop and deploy NLP models to extract insights from unstructured text data Expertise in statistical analysis data visualization and data preprocessing techniques Build and deploy deep learning solutions for time-series tabular and unstructured data e g text from contracts invoices Integrate Generative AI and Agentic AI frameworks e g LangChain ReAct Hugging Face Transformers to create autonomous or semi-autonomous agents that enhance decision-making Collaborate with data engineers and business stakeholders to translate supply chain pain points into production-grade analytics solutions Own the end-to-end ML lifecycle from data preparation to model validation deployment and post-launch performance monitoring Apply optimization and operations research techniques to solve routing sourcing and capacity planning problems Required Qualifications 5 years of hands-on experience in data science with a focus on S OP supply chain manufacturing or logistics preferred Deep expertise in machine learning regression classification clustering time-series deep learning CNNs RNNs Transformers and reinforcement learning Proven experience with Generative AI e g GPT diffusion models and Agentic AI or multi-agent systems Advanced programming skills in Python with experience in ML libraries PyTorch TensorFlow Scikit-learn XGBoost Hugging Face etc Experience with cloud platforms AWS GCP Azure containerization Docker and deployment pipelines Strong business acumen and the ability to align technical solutions with supply chain goals and KPIs Excellent communication skills with the ability to distill complex ideas for diverse continuously track emerging AI ML trends and evaluate their relevance to supply chain strategy and automation Coach junior data scientists and shape the internal data science best practices Essential Desirable Education Qualifications Work experience technical skills i e what are the must haves for this role Experience with real-time analytics and streaming data Kafka Spark Hands-on experience with LangChain OpenAI API or ReAct AutoGPT-style architectures Familiarity with optimization techniques e g MILP heuristics Knowledge of NLP use cases in supply chain S OP contract parsing vendor correspondence part classification Education PG BE B Tech in Computer Science Data Science or a related field from a Tier 1 or Tier 2 institution A Master s degree in a relevant field is preferred but not mandatory