Data Scientist (Manufacturing)

The Data Scientist will build and implement advanced analytics solutions for manufacturing challenges including process optimization, production yield improvement, quality prediction, equipment reliability, and energy efficiency. Responsibilities include analyzing complex datasets using EDA, statistical methods, and machine learning algorithms, incorporating engineering and process-domain knowledge, deploying and monitoring scalable ML solutions, leading and mentoring a small team, partnering with manufacturing and operations teams, and driving the complete analytics lifecycle. The team fosters an inclusive, growth-oriented culture where continuous learning and knowledge sharing are actively encouraged across all levels. The role offers the opportunity to work within a collaborative, cross-functional team environment, contributing to end-to-end project delivery and continuous process improvement initiatives.

5+ years of experience in Data Science with demonstrated success in manufacturing, process, energy, or industrial environments. Strong programming skills in Python with Pandas, Scikit-learn, XGBoost, Pyomo. Experience with cloud-based ML platforms such as Azure ML or AWS SageMaker. Understanding of industrial automation systems and mathematical optimization. B.Tech/B.E. or M.Tech/MS/M.Sc/MCA. A collaborative mindset, willingness to mentor junior team members, and adaptability to changing business needs are highly valued for this role. Prior experience working in global delivery models, along with exposure to Agile methodologies, will be considered an added advantage.