Vinod K.

A highly analytical and detail-oriented Data Analyst with a strong foundation in data science, acquired through rigorous academic training at IIT Roorkee and practical experience in real-world projects. Vinod has successfully applied statistical methods and machine learning techniques to solve complex business problems, including a telecom churn prediction project that utilized Principal Component Analysis (PCA) and logistic regression. With a passion for deriving actionable insights from data, Vinod excels in transforming raw data into meaningful metrics that drive decision-making. He is proficient in using tools such as Python, SQL, and Excel for data manipulation, analysis, and visualization. His keen interest in identifying patterns and trends makes him an asset in any data-driven environment. Vinod is particularly focused on opportunities in the fashion retail sector, where his ability to analyze consumer behavior, market trends, and operational efficiency can significantly contribute to a company's success.