Nagam Prasad

Data Science-focused Data Analyst specializing in building, evaluating, and comparing machine learning models (regression, classification) from raw data to stakeholder-ready insight. Proven track record delivering end-to-end analysis — data cleaning, EDA, feature engineering, and model evaluation — on live business datasets, most recently achieving 94% classification accuracy on a real-time ML pipeline. Actively growing into agentic AI and LLM-based systems (prompting, tool use, RAG pipelines), backed by a Data Science with AI certification and consistent Git/GitHub-tracked project work.

Data Science Intern - Cognifyz IT Solutions Pvt. Ltd.

• Remote

(2026-05 - 2026-06)

• Completed end-to-end Python-based analysis on a restaurant industry dataset — statistical analysis, geospatial analysis, and feature engineering — to identify pricing, cuisine, and service patterns across a live business dataset of 9,500+ records.
• Built and compared multiple ML regression models (linear regression, decision tree, random forest) to predict restaurant ratings from engineered features, improving prediction accuracy by 15% over baseline; used cross-validation to select the best-performing regressor.
• Engineered 12 new features from raw location, pricing, and cuisine data to boost model signal, and presented findings in a structured report translating results into pricing and service recommendations for stakeholders.

B.Tech - Computer Science Engineering - Kakinada Institute of Engineering and Technology (2021 - 2025)