Prince Chandra

• Created internal Python libraries to facilitate portfolio construction.
• Performed comprehensive time series analysis for novel research initiatives in factor investing and index development.
• Analyzed historical market data employing diverse portfolio construction tools.
• Optimized the index rebalancing workflow and authenticated rebalancing outcomes utilizing Python and SPEL.

• Discovered regions of interest (ROI) zones for renewable resource infrastructure through machine learning approaches.
• Identified lung diseases with a custom-built CNN architecture, achieving a 95% accuracy rate.
• Forecasted seismic risk zones utilizing clustering techniques, and estimated earthquake magnitudes employing regression methods.

• Investigated behavioral data to analyze post-error slowing response times in mice, examining the influence of external and internal conditions like temperature, lighting, attention span, contrast level, and session phase.
• Conducted regression analysis resulting in a 95% Mean Squared Error (MSE) score attainment.

• Acquired hands-on experience in utilizing Python for data analysis, SQL for database querying, and implementing functionalities within the AWS cloud infrastructure.

• Developed a ml model using regression techniques to predict payment dates and classify invoices into different payment timeline groups based on the anticipated payment dates.
• Created an Invoice Bill Management Application using ReactJs and Java, enabling different functionalities within the system.
• Seamlessly integrated a machine learning model to enhance the application capabilities.

• Conducted exploratory data analysis (EDA) to examine the correlation between students’ test scores and factors such as gender, ethnicity, parental education level, lunch, and test preparation courses.
• Constructed a regression-based machine learning model to forecast the prices of pre-owned cars using Kaggle data, achieving a 92% R2 score.