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Rakshana Sundaram

@rakshanasundaram

AI and data science intern at STUDOR who built a job recommender combining O*NET skills, live Google Jobs results, and resume-fit analysis.

India

Message

At STUDOR, I built a job recommender that combines an open-jobs corpus with O*NET skills and live Google Jobs results. I used Gemini-extracted skills and embedding similarity to score resume-job fit, then shipped a FastAPI app with skills-gap and eligibility analysis.

At IIT Bombay, I contribute to data and AI projects including a course recommender for undergraduate students and a webmail assistant with calendar integration. As Overall Team Head of UGAC's Data Analytics and Visualization Team, I launched the institute-wide Grading Statistics Report 3.0 and am developing CareerGPT.

Experience

Work history, roles, and key accomplishments

Current

Overall Team Head

Current

Data Analytics and Visualization Team, UGAC, IIT Bombay

Apr 2026 - Present (6 months)

Led recruitment for a 9-member team, launched the Grading Statistics Report 3.0, and developed CareerGPT, a LangChain-based ReAct agent with RAG for placement and internship resources.

Leadership Recruitment Lang Chain LangGraph ChromaDB RAG Data Analysis Statistical Graphs

Data Science Intern

STUDOR

May 2026 - Jul 2026 (2 months)

Selected through IIT Bombay Placement Cell to intern at a US-based EdTech company. Interviewed immigrant job seekers to identify user needs, built a job recommender with O*NET skill taxonomy, and shipped a FastAPI app for resume-job fit analysis.

Python fastAPI O*NET Gemini Text Embedding 3 Small Semantic Caching (GPTCache)Google For Jobs Cosine Similarity API Optimization

Data Analyst

Data Analytics and Visualization Team, UGAC, IIT Bombay

Jun 2025 - Mar 2026 (9 months)

Part of a 9-member team providing data-driven solutions. Created a database of 1,000+ courses, designed a feedback survey on the FCFS registration process, and prepared the institute-wide FCFS report.

Web Scraping Data Analysis Survey Design Python MySQL Reporting