Currently an Extern @Pfizer
Learning applied AI through projects and a Pfizer externship, aiming to build real-world skills and confidence.
Portfolio of coursework and hands-on projects focused on AI, data extraction, and document insights from a Pfizer externship and other learning work.
Analyzed 17-season IPL dataset (260K+ records) to surface actionable batting, bowling, and venue trends across 6 visualizations, merging multi-table delivery and match metadata using Pandas; applied groupby, filtering, and crosstab normalization to uncover insights including Kohli's all-time run lea
Built an AI-powered text transformation tool integrating the Google Gemini API to reconstruct informal input into structured, professional prose; engineered a Python-based backend service via Gemini REST API integration and designed a prompt pipeline to transform unstructured text into structured JS
Learning applied AI through projects and a Pfizer externship, aiming to build real-world skills and confidence.
I am Parth Nayyar, a first-year Data Science student pursuing a bachelors degree with a focus on artificial intelligence. I have limited professional experience and am looking to build real-world confidence through project-based learning, including a Pfizer externship on AI-powered document insights and data extraction.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
Pfizer
Education
Mahindra University, Hyderabad
B.Tech in Data Science · Class of 2029
Skills
Analyzed 17-season IPL dataset (260K+ records) to surface actionable batting, bowling, and venue trends across 6 visualizations, merging multi-table delivery and match metadata using Pandas; applied groupby, filtering, and crosstab normalization to uncover insights including Kohli's all-time run lea
Built an AI-powered text transformation tool integrating the Google Gemini API to reconstruct informal input into structured, professional prose; engineered a Python-based backend service via Gemini REST API integration and designed a prompt pipeline to transform unstructured text into structured JS
Built a Python CLI tool for PDF management featuring AES-based encryption, multi-file merging, and automated document splitting; supported batch processing of multiple files via command-line arguments using a modular Python architecture separating encryption, merge, and split functions.
