Machine learning engineered for deterministic industrial impact.

Data Scientist · Nov 2019 – Apr 2023 (3 yrs 6 mos) · Bangalore, India

Developed AI-powered applications to enhance manufacturing product quality, optimize defect detection, and maximize process efficiency.

• Led end-to-end development of an AI-driven system to identify root causes of defects, generating preventative rules for production scheduling.
• Developed a decision tree-based defect diagnosis system generating multiple optimal and alternative decision rules with automated visuals for end-user interpretability.
• Designed and developed a Quality Precognition system predicting stage-wise defects using Random Forest and SHAP model interpretability to isolate top defect drivers.
• Engineered machine learning (Random Forest) and deep learning (Neural Networks with Transfer Learning) models predicting steel coil mechanical properties (Yield, Tensile, Elongation), simulating process recipes to slash quality variability.

Data Science Intern · Jul 2019 – Oct 2019 (4 mos) · Bangalore, India

Researched and built anomaly detection algorithms for high-throughput sensor telemetry.

• Developed an Outlier Detection System for high-frequency sensor data utilizing statistical and machine learning models, laying foundation for patent filing.

R&D Intern · Aug 2018 – Jul 2019 (1 yr) · Bangalore, India

Engineered predictive monitoring infrastructure for clinical healthcare systems.

• Developed ETL processes and pipelines using ELK Stack to enable proactive and predictive monitoring of PACS (Picture Archiving and Communication System).
• Conducted data extraction, preprocessing, and visualization to facilitate data-driven decision-making.
• Utilized Decision Tree models to predict medical image transmission latency across PACS networks.