Portfolio

Highly analytical and detail-oriented Data Analyst with a strong foundation in data analytics and software development, seeking to leverage expertise in predictive modeling and statistical analysis to drive energy forecasting and business planning. Proficient in Python, SQL, and data visualization, with a proven track record of delivering actionable insights for informed decision-making

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Predicting Accident Severity

This project aims to predict the severity of accidents by analysing various factors such as location, collision type, and number of vehicles involved. The goal is to develop a model that can warn users about potential hazards and help them make informed decisions about their travel plans.

Loan Applicant Clustering and Analysis

This project applies dimensionality reduction techniques like Principal Component Analysis (PCA) and clustering algorithms like K-Means to group loan applicants based on their financial attributes. The analysis includes interpreting the clusters, evaluating cluster quality, and visualizing the result

Asset Portfolio Optimization

The project involves analyzing monthly price data of five assets and a corresponding factor value column to predict portfolio returns. Mean-Variance Markowitz models are utilized to evaluate various risk-return scenarios and identify optimal asset allocations.

Customer Churn Analysis

This project involves preprocessing and analyzing a dataset related to customer behavior and demographics. Techniques such as data manipulation, missing value handling, data preparation, feature selection, modeling using SVM are applied to predict customer behavior and assess model performance.

Sayanth Rathnendranath

Portfolio

Predicting Accident Severity

Loan Applicant Clustering and Analysis

Asset Portfolio Optimization

Customer Churn Analysis

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