Aditya Sharma

Helped energy sector clients optimise trading, pricing, and hedging decisions by developing and implemented scalable predictive analytics products for clients in the energy sector with 97% accuracy with 3 flagship products – load forecasting, load disaggregation, core analytics. Spearheaded analytical products into markets with high solar technology penetration, developed solar irradiance forecast using Support Vector Regression with astronomical and meteorological variables. Enabled clients identify, rooftop solar and solar load forecasting using Gradient Machine Boosting. Translated effects of growing Electric Vehicle market into EV identification by developing load consumption behaviour models. Developed support vector machine model for charging demand prediction. Improved forecasting accuracy by developing load clustering modules for improved load profile identification. Implementation of K-means clustering via PCA and Silhouette analysis. Developed Regularization (Ridge) models to address over-fitting in the highly sensitive feature engineered variables. Developed a Smoothing mechanism using local weighted regression. Developed anomaly detection algorithm for deployment into preprocessing workflows.

Performed exploratory data analysis (correlations, scatter plots, histograms, etc.) and Regression to understand multiple vicinity factors influencing the price in the housing industry. Worked on Market research, data analysis projects.