MSAT - Data Science

Key Responsibilities for MSAT - Data Science.

1. 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.

2. PAT Strategy & Multivariate Process Monitoring

• Design 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

3. Technical Lead

• Act 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 & Technologies

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