I grew up fascinated by how systems work — which led me to pursue a B.Tech in Engineering at IIT Madras, one of India's premier technical institutions. There, I built a deep foundation in mathematics, statistics, and algorithms — and developed a taste for turning complex, messy data into decisions that actually matter.
During my undergrad, I joined Seat of Joy — a child safety startup incubated at IIT Madras — as a Business & Strategy Analyst. I built a probabilistic market-sizing model from Indian Census data (100+ tables, 200K+ rows each) that estimated 55M target customers with 5% YoY growth, developed a supply-chain optimization model using operations research principles, led full competitor and pricing analysis across the category, and represented the startup at Shark Tank India Auditions — pitching data-backed market and business strategy to investors.
I'm now pursuing my Master of Science in Business Analytics (MSBA) at UCLA Anderson, deepening my expertise in machine learning, data engineering, and optimization. I'm drawn to problems where rigorous analysis drives real-world impact — from production agentic RAG systems to large-scale data pipelines to deep reinforcement learning.
Seat of Joy (Incubated at IIT Madras)
Child safety startup developing a full-body protective seat for two-wheelers — addressing the 2 children lost daily in India to two-wheeler accidents.
India · During Undergrad
A selection of data science and ML engineering work.
Production-deployed agentic RAG system for UCLA MSBA students to query course materials — lecture slides, transcripts, and PDFs — using natural language. Live at tirth-courserag.duckdns.org.
MotivationThe UCLA MSBA program runs 4 simultaneous courses, each with its own slides, transcripts, homework deadlines, and deliverables spread across a shared Google Drive. Students constantly lose time hunting for information manually. I built a fully agentic system that classifies every query, self-verifies deadline answers, supports human-approved file uploads, and can explain exactly which source chunks drove any answer — deployed at effectively zero infrastructure cost on Oracle Cloud Free Tier.
End-to-end data engineering pipeline correlating weather patterns with Yelp restaurant sentiment using PySpark, Snowflake, Airflow, and Tableau — processing 10M+ records.
MotivationCurious whether weather drives restaurant ratings and business patterns, I built a production-grade data pipeline ingesting the full Yelp Academic Dataset and OpenWeatherMap API, performing distributed ETL at scale, NLP sentiment scoring, and surfacing insights through an executive Tableau dashboard.
Deep reinforcement learning agent that solves the Maltese Gear Cube using a CUDA-accelerated neural heuristic.
MotivationTo apply the DeepCubeA algorithm to a novel, higher-complexity puzzle and validate whether deep RL can generalize to unseen combinatorial state spaces.
Interactive Tableau visualization analyzing COVID-19's impact on India — tracking vaccination rollout, weekly case surges, and death rate trajectories with demographic context.
MotivationTo quantify the pandemic's real-world effects on India through vaccination rates, case trajectories, and death rates — contextualised by demographic indicators like HDI, median age, and population density — and surface actionable patterns through interactive Tableau dashboards built entirely from joined public datasets.
Multi-dashboard Tableau analytics dissecting seller performance, shipping logistics, and product characteristics across 89K+ e-commerce orders — revealing revenue concentration, delivery patterns, and cost structures.
MotivationTo provide a comprehensive analytical view of e-commerce operations by building interconnected Tableau dashboards that dissect seller performance, shipping efficiency, and product characteristics — enabling data-driven decisions on seller management, logistics optimization, and pricing strategy.
The tools and technologies I work with.
Whether you're recruiting, collaborating, or just want to talk data — my inbox is always open.