Key Responsibilities

Data Science & Analytics Solutions

- Build and implement advanced analytics solutions to address manufacturing challenges, including process optimization, production yield improvement, quality prediction, equipment reliability, and energy efficiency.
- Analyze complex datasets using exploratory data analysis (EDA), statistical methods, and machine learning algorithms to generate actionable business insights.
- Incorporate engineering and process-domain knowledge into analytical models by developing meaningful features and business constraints.
- Deploy, monitor, and maintain scalable machine learning solutions across on-premise and cloud platforms, ensuring reliability and operational performance.

Leadership & Team Development

- Lead and mentor a small team of data scientists, providing technical guidance, task prioritization, and performance oversight.
- Drive the complete analytics lifecycle, from business problem identification and solution design to model validation, deployment, performance monitoring, and continuous improvement.

Cross-Functional Collaboration

- Partner with manufacturing, operations, business leaders, and support functions to identify improvement opportunities and translate them into data-driven solutions.
- Work closely with Data Engineering and IT teams to build secure, scalable, and reliable data pipelines and production-ready analytics environments.

Model Governance & Solution Management

- Take ownership of deployed analytical solutions by maintaining comprehensive documentation, version control,



and governance standards.
- Establish model performance metrics, monitor accuracy and business impact, identify model drift, and implement enhancements to sustain long-term value.

Required Qualifications

- Minimum 5 years of experience in Data Science, with demonstrated success in delivering analytics solutions for manufacturing, process, energy, or industrial environments.
- Proven expertise in managing end-to-end machine learning projects, from data acquisition and model development through deployment and measurable business outcomes.
- Bachelor's or Master's degree in Data Science, Computer Science, Applied Mathematics, Chemical Engineering, Mechanical Engineering, or a related quantitative discipline.
- Strong programming skills in Python with hands-on experience using libraries such as Pandas, Scikit-learn, XGBoost, Pyomo, and similar frameworks.
- Experience with cloud-based machine learning platforms such as Azure Machine Learning, AWS SageMaker, or equivalent technologies.
- Valuable understanding of industrial automation systems, including DCS, SCADA, OPC UA, historian databases (OSI PI, Aspen IP.21), and time-series data analytics.
- Experience in mathematical optimization techniques, including Linear Programming (LP), Mixed Integer Linear Programming (MILP), or Mixed Integer Nonlinear Programming (MINLP), will be considered an added advantage.

PLEASE NOTE THIS POSITION IS PURELY ON SITE/ OFFICE BASED, WFH AND REMOTE WORK IS NOT SUPPORTTED . PLEASE APPLY KEEP IN MIND

📌 Data Scientist (New Delhi)
🏢 Hr Services Chandigarh
📍 New Delhi