Mahesh Bhosle

Collected, cleaned, and preprocessed structured datasets using Python, Pandas, and Excel to support analytical workflows. Performed exploratory data analysis (EDA) and statistical analysis to derive actionable business insights. Developed interactive dashboards and reports using Power BI and Excel for KPI monitoring and business performance analysis. Automated data processing and reporting tasks, improving efficiency and reducing manual effort. Built and integrated Retrieval-Augmented Generation (RAG) pipel

Optimized data mining pipelines under memory constraints, using Docker containers to extract behavioral features from 85,000 node graphs with a 22.4% reduction in batch processing time. Programmed advanced clustering protocols and boosting methods, aggregating 450,000 data points to construct a preliminary social graph framework engineered for downstream analytics at scale. Leveraging specialized data structures alongside rigorous statistical modeling, enhanced the precision of internal predictive models by

Applied supervised and unsupervised ML techniques to real-world datasets as part of a structured data science programme. Built and evaluated classification and regression models using scikit-learn, with hands-on work in data preprocessing, feature engineering, and model validation. Completed a comprehensive certification in data science covering the full ML pipeline.

Master's programme covering advanced topics in machine learning, data science, algorithms, and computer science fundamentals. Coursework includes AI system design, statistical learning, and applied data engineering. Actively applying academic knowledge through practical projects in generative AI an

German Grade:- 1.4