Pfizer Externship via Extern
I have some hands-on work experience and I am sharpening skills through real projects while looking for the right first full-time role.
Curated examples of projects I worked on that show the skills I am building and the kinds of problems I like to solve.
Owned the system end to end — requirements through development, deployment and ongoing support — live on a public domain, including build, release and post-launch fixes. Built the front end in React and TypeScript: screens, interactive components and reusable UI, integrated with REST services return
Built a full pipeline — ingestion, preprocessing, modelling and evaluation — reaching an F1-score of ~0.85, deployed as a Flask web service with performance monitoring in production.
I have some hands-on work experience and I am sharpening skills through real projects while looking for the right first full-time role.
I am a full-stack software engineer with over a year of experience building enterprise web applications for clients worldwide. I use React, Next.js, and Angular with TypeScript for the front end, and Node.js and NestJS for the back end, along with MySQL and Microsoft SQL Server databases that I designed. I have deployed AWS services like Lambda and S3, monitored through CloudWatch. I created WildAtlas, taking it from concept to launch, and I hold a Master of Data Science, where I built Python da
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
In progress
Experience
Software Engineer (Full Stack) — Trigent Software Solutions
Trigent Software Solutions · Nov 2022 – Jan 2024
Education
Monash University
Master of Data Science · Class of 2026
Visvesvaraya Technological University, India
Bachelor of Engineering — Computer Science · Class of 2022
Skills
Owned the system end to end — requirements through development, deployment and ongoing support — live on a public domain, including build, release and post-launch fixes. Built the front end in React and TypeScript: screens, interactive components and reusable UI, integrated with REST services return
Built a full pipeline — ingestion, preprocessing, modelling and evaluation — reaching an F1-score of ~0.85, deployed as a Flask web service with performance monitoring in production.
Built a complete data and modelling pipeline reaching up to 95% validation accuracy, deployed as a Flask web app for real-time inference.
✅ Verified by Extern · ⏱️ In progress
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
The project developed a prototype pipeline combining OCR, large language models, and retrieval-augmented generation to extract structured data and surface document insights from enterprise PDFs. The work surveyed LLM capabilities, integrated OCR outputs with embedding-based retrieval, and produced example queries and extracted fields from sample documents.
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I produced a written explanation of LLM internals, detailing tokenization, attention mechanisms, and how models generate the next token from context.
I described LLM internals: how tokenization breaks text into tokens, how attention mechanisms build contextual understanding, and how the model generates the next token from that context.
During the externship I built and ran a Colab notebook that implemented Python fundamentals, cleaned tabular data with Pandas, parsed nested JSON into DataFrames, applied text standardization, and performed image preprocessing steps for improved OCR accuracy.
