Shaurya Chawla

New Delhi

Summary

Entry-level GenAI & Data Science professional with hands-on experience in RAG systems, LLM-powered applications, an python based development. Strong focus on practical, production-oriented AI, clean code, and research-to-deployment pipelines. Seeking junior/entry-level tech roles .

Work History

Financial Systems Developer Intern

ZeTheta Algorithms Private Limited

New Delhi

01.2026 - Current

Working on a BFSI-focused live project involving the design and development of auction-based financial systems using Python.
Designed and implemented auction mechanisms (Dutch, English, sealed-bid) and allocation logic.
Used LLMs and Retrieval-Augmented Generation (RAG) for financial research, rule modeling, and strategy simulation.
Built bidding strategy simulators, analytics modules, and dashboards for treasury and IPO-style scenarios.
Conducted winner's curse analysis and explored risk mitigation strategies using data-driven insights.
Followed a full end-to-end engineering workflow: research → system architecture → implementation → testing → documentation.
Gained real-world exposure to financial systems, AI-assisted engineering, and production-grade problem solving.

Education

B.S. - Computer Science

San Francisco State University (SFSU)

USA

08-2025

Skills

Programming: Python (Advanced), SQL (Basic)

AI / GenAI: LLMs, Retrieval-Augmented Generation (RAG), Prompt Engineering, AI-assisted development Data Science: pandas, NumPy, scikit-learn, Data Analysis

Web & Apps: Flask, Streamlit, HTML/CSS/JS

Tools: Git, GitHub, Jupyter, APIs Domains: BFSI systems, Financial auctions, NLP applications

Websites

Projects

Document Reader Chatbot (RAG) [Jan 2026 ]

GitHub: shauryachawla15/Document-reader-chatbot-RAG

● Built a PDF-based document question-answering chatbot using Retrieval-Augmented Generation (RAG). ● Ensured responses are generated strictly from document content, minimizing hallucinations.

● Implemented end-to-end RAG pipeline: document ingestion, chunking, embedding, retrieval, and response generation.

● Strengthened understanding of LLM grounding, retrieval strategies, and context management.

Tech: Python, RAG, NumPy, LLMs, AI

Sydney Events Web Scraper & Streamlit App [Jan 2026]

GitHub: shauryachawla15/sydney-events-mvp

● Developed a Python-based web scraping system to automatically collect live event data.

● Built a Streamlit web application to display events in a clean, minimal UI.

● Implemented user flow for ticket redirection and email capture.

● Designed system to auto-update events as new listings appear on source websites.

Tech: Python, Web Scraping, pandas, Streamlit, Data Science

Timeline

Financial Systems Developer Intern

ZeTheta Algorithms Private Limited

01.2026 - Current

B.S. - Computer Science

San Francisco State University (SFSU)