Northeastern University · Boston, MA
Economics and Finance student at Northeastern with a Data Science minor. This site is where my résumé, projects, and occasional writing live. Where it's all headed, I'm still working out.
Applied, and got the email. Joining the e-board as Treasurer, with the role kicking off in the fall. Time to put the finance concentration to work on an actual budget.
Cleared the NISM mutual fund distributors exam and am now a registered mutual fund distributor in India. The Nirmal Bang stint, now with a licence behind it.
Built and deployed two tools with Python and Streamlit: an interactive DCF — pull a ticker, adjust assumptions, get a valuation — and a multi-factor stock screener. First projects in a longer finance-AI roadmap.
Short stint in the sales department at Nirmal Bang, a stock brokerage in Bombay. Learnt a lot about how mutual funds actually get sold — the pitch, the pushback, and everything in between.
Through Khoury College, placed into CS 2000. The logic: data science maps directly onto where finance is going (Python, stats, ML) without needing a CS background first.
Pitched OmniRetail at a campus venture pitch night with a full deck, memo, and speaker notes. Lost by one vote. Still mad about it.
Interactive discounted cash flow valuation for any public company. Adjustable growth, margin, and WACC assumptions with live data via yfinance.
Pulls earnings call transcripts and uses AI to extract tone, guidance changes, and what management is avoiding saying.
Custom multi-factor screener: value, quality, and momentum filters across global equities.
Mean-variance and risk-parity portfolio construction with constraint handling and backtesting.
Slowly, then all at once. Why I'm betting my degree on the overlap between the two.
You don't understand a model until you've had to handle its edge cases in code.
Handing the wheel to a model: what autopilot investing actually looks like, and whether you should trust it.
I'm a student at Northeastern's D'Amore-McKim School of Business, studying Economics and Business Administration with a Finance concentration and a Data Science minor. The thesis behind that combination: the analysts who'll matter are the ones who can both build the model and build the tool that builds the model.
Right now most of my energy goes into a finance-AI project roadmap: tools that do real analyst work, built in Python and shipped publicly. I haven't locked in exactly where I want to end up yet, and this site is partly how I figure that out, by building things and seeing what sticks.
Off the desk: in the gym chasing an Arnold-in-'75 physique (results may vary), on the squash court, and listening to house music.