MEENAKESHWAR RAO NIDADHANA

Dynamic Data Science professional with a robust background in data visualization and machine learning. Proficient in Python, SQL, Power BI, and Tableau, delivering predictive modeling and actionable insights that optimize operational efficiency. Achievements include driving revenue growth through innovative solutions across diverse industries. Currently advancing expertise through a Master’s in Data Science and Applications at the University at Buffalo.

·  Designing and implementing a robust IDBMS for Desi Insurance Company to centralize data management, enhance operational efficiency, and ensure compliance with industry regulations, improving data security and customer service. Book Sales Analysis and Prediction (Machine Learning) University at Buffalo, NY | 2024

Implementation of an Insurance Database Management System (IDBMS) University at Buffalo, NY | 2023

·  Developed a predictive model to forecast book sales using historical data sourced from Kaggle. Conducted data preprocessing, normalization, and statistical analysis, and implemented machine learning models including Random Forest and Linear Regression. Achieved high accuracy (R² = 0.93) with the Random Forest model, providing actionable insights for publishers on consumer preferences and inventory management.

Big Data Analytics using Hadoop and Spark: Java, Hadoop, HDFS, Spark University at Buffalo, NY | 2024

· Derived N-gram word co-occurrences along with lemmatization from a large-scale Latin text data utilizing MapReduce and Spark.

REPOS ENERGY APPLICATION

·  Developed a Doorstep Diesel Delivery application, streamlining fuel delivery with features such as location and quantity tracking, integrated payment options, and detailed performance analytics. Leveraged Python for backend development, SQL for database management, and Power BI for creating insightful dashboards and reports. This initiative enhanced customer convenience, expanded the client base, increased application downloads, and significantly contributed to revenue growth of the organization.

BRANE ENTERPRISES

·  Leveraged Python, Machine Learning, and Cloud technologies to drive the creation of an innovative image-to-text extraction application for Lennox, expediting contract renewal processes and resulting in a $300,000 revenue increase. We used SQL and Tableau to evaluate and present project impact metrics.

·  Designed and built a full solution for Market Yard in Algeria, leveraging Python, R, and MySQL to streamline sales and buy procedures for farmers and wholesalers, resulting in a $50,000 revenue increase. Outstanding project performance resulted in the acquisition of a high-value project from Asset 360, effectively doubling the original project's revenue.