Process Engineer transitioning into corporate analytics and data science roles with specialization in manufacturing stability, risk quantification, and interpretable modeling for industrial systems.

• Process Stability & Variability Analytics
• Time-Series Feature Engineering
• Control Deviation (SP–PV Gap) Analysis
• Risk Regime Segmentation
• Interpretable Logistic Regression Modeling
• Industrial Data Governance & Anonymization

• Solar Ingot Puller Operations
• Crystal Growth Process Stability
• Equipment Telemetry Analytics
• Six Sigma Documentation & Process Risk Analysis
• Manufacturing Process Optimization

Structured pipeline for quantifying instability using engineered variability, drift, and control deviation features with regression-based validation.

Generalized approach for identifying concentrated performance degradation drivers using interpretable statistical methods.

• Python (pandas, numpy, scikit-learn, matplotlib)
• Statistical Modeling & Validation
• Feature Engineering for Industrial Time-Series
• Process-Oriented Data Structuring
• Risk Segmentation & Diagnostic Analytics

Seeking corporate roles in:

• Process Analytics
• Data Analytics / Data Science
• Industrial Digital Transformation
• Semiconductor / Solar / Battery Manufacturing Analytics