Satyam Kulkarni

Developed an Excel dashboard for analyzing movie success factors and a Tableau dashboard for manufacturing trends. I also applied predictive analytics on bank data using Hadoop, Hive, and PySpark, and built deep learning models for facial emotion recognition and e-commerce CSAT score prediction. Implemented a time series model to forecast HDFC Bank stock prices and conducted exploratory data analysis (EDA) to identify churn drivers in the telecom sector.

Conducted ANSYS simulations for client structural analysis team Cummins Turbo Technologies, optimizing automotive product designs using Design of Experiments (DoE), reducing computational time and resource usage by 50%. Collaborated with cross-functional teams, delivering technical insights through reports and visualizations; occasionally used SQL and Python for data analysis and machine learning for predictive material analysis.

With specialization in Artificial Intelligence and Machine Learning, pursuing a Master of Science degree worth 90 ECTS credits (2,250 hours of study), recognized at Level 7. Projects: Developed a Power BI dashboard to analyze adverse event reports from the FDA's CFSAN Adverse Event Reporting System (CAERS) dataset, End-to-end machine learning model to forecast retail sales and AI chatbot utilizing Large Language Models (LLMs) to provide personalized financial advice.

Developed MATLAB program for automating iterative calculations, enhancing design efficiency for BAJA vehicle gearbox.