Kirtan Shah
Data Scientist
Remote (global)
LinkedIn profile available to registered employers
Self-assessed English levels
Artificial Intelligence-Based Hull Potential Prediction System
Developed regression-based machine learning models using Python, WEKA, and Excel to predict Hull Potential in Impressed Current Cathodic Protection (ICCP) systems from operational ship datasets. Performed data preprocessing, feature engineering, and evaluated multiple regression algorithms including Linear Regression, Decision Tree, Random Forest, and Random Committee. The Random Committee model achieved the best performance with a Correlation Coefficient of 0.9159, MAE of 6.5767, and RMSE of 42.7554, demonstrating its effectiveness for hull potential prediction and predictive maintenance.
Stock Market Analysis & Visualization
Conducted exploratory data analysis and statistical evaluation of historical stock market data using Tableau and Excel. Applied Exponential Moving Average (EMA) and Relative Strength Index (RSI) to identify market trends and developed interactive dashboards for effective financial data visualization and investment analysis.
Distribution Payment Analysis:
Developed an analytical reporting solution using SQL, Tableau, and Excel by extracting, validating, and analyzing distributor payment data. Created interactive dashboards to monitor regional sales performance and payment trends, delivering actionable insights that enhanced payment tracking and supported operational decision-making.