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
