MSAT - Data Science

Key Responsibilities for MSAT - Data Science.

• Machine Learning Lead the design, development, and validation of advanced Machine learning models for improving process efficiency.Drive methodological decisions related to feature engineering, variable selection, model tuning, and robustness testing.
• PAT Strategy & Multivariate Process MonitoringDesign and implement PAT analytics frameworks for real-time and near-real-time process monitoring.Interpret and analyze time-series, batch, and sensor-based data (e.g., NIR, Raman, process variables).Expertise in Performing MVDA (BEM & BLM) analysis in SIMCA software
• Technical LeadAct as a technical lead for PAT, chemometrics, and ML initiatives.Collaborate closely with process engineers, manufacturing, quality, and business stakeholders.Translate complex analytical results into clear, actionable recommendations for decision-makers.Mentor junior data scientists and contribute to capability building across the team.

Tools & TechnologiesProgramming & Analytics: Python (NumPy, Pandas, SciPy)ML & Chemometrics: scikit-learn, XGBoost, TensorFlow/PyTorch, custom PCA/PLS frameworksVisualization & Analysis: Jupyter, MVDA tools, SIMCA Bach evolution Modeling and Batch Level ModelingData Types: Spectral data, time-series, batch and manufacturing process data