Karthik Kumar Raghumurti Bhat

• Designed and implemented a job-based course recommendation system for over 10.000 users using Python, TensorFlow, and PyTorch. • Utilized Named Entity Recognition (NER) to extract skills from job advertisements and course descriptions. • Applied Natural Language Processing (NLP) to map relationships between job requirements and learning resources thereby creating a graph. • Collaborated with Data Science experts to develop course recommendation system using state-of-the-art machine learning techniques.

• Developed efficient data models within SAP S/4 HANA, yielding a 50% reduction in processing time and notable enhancements in data accuracy. • Utilized SQL procedures to refine current data models, resulting in a 60% improvement in performance and efficiency. • Successfully migrated the data models from SAP HANA to C4S, amplifying data processing capabilities and accessibility for machine learning endeavors. This initiative sustainably increased the efficiency and improved the overall productivity.

• Developed and maintained ETL pipelines in Azure for radar data ingestion, validation, and transformation. • Conducted exploratory data analysis (EDA) using statistical methods and performed feature engineering to improve ML model accuracy. • Built and deployed ML models for radar classification using logistic regression and ensemble techniques. • Deployed NLP-based Smart Feedback System in Azure, enabling real-time sentiment analysis.

• Developed ETL pipelines using Azure DataFactory, Databricks, and PySpark, storing data in Azure Data Lake. • Created Python tools for replaying RF sensor threat warnings in fighter jets for sortie analysis. • Updated radar database modules in C++ for defense platform requirements. • Executed SQL scripts in PostgreSQL and Oracle, and developed software modules to monitor RWR system health.