Prakhar Srivastava

I've never been able to do just one thing. Turns out, that's the point.

Finance  ·  Strategy × Product × Data  ·  NYU MS '26

Engineer turned product builder turned finance researcher. I read a balance sheet, write a PRD, and run a growth experiment with the same instinct — the whole board, before the move. Finance is where it all finally points.

See how I got here ↓ The Work
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The Story So Far

How one path
became many.

I
2018 – 2022 · B.M.S College of Engineering, Bangalore

Where It Started

A B.E. in Computer Science — and a habit of asking "why," not just "how."

I trained as an engineer: Computer Science, Big Data, Data Science. But even then I was less interested in the code than in what it was for — the business behind the build, the money behind the system. I learned to make things work at scale. I also learned that I'd never be satisfied owning just one layer of the stack.

II
2022 – 2024 · Koch Business Solutions

The Machinery of Money

Where engineering met finance for the first time.

I wasn't just writing code — I was redesigning how multi-billion-dollar financial processes actually move. RPA, OCR, SAP. Order-to-cash. Procure-to-pay. I shipped 22 automation products end to end, saved roughly $250K a year, and cut workflow failures by 80%. The lesson that still drives me: behind every workflow is a decision, and behind every decision is data someone wasn't reading properly.

III
2024 – 2026 · New York University

Going to New York

I came for the credential. I stayed for the obsession.

An MS in Information Systems at NYU. Corporate Finance, Valuation, Data Science, AI for Business, Digital Strategy. I stopped being someone who automated finance and started becoming someone who understood it — the why underneath the workflow. The city has a way of turning curiosity into appetite.

IV
2025 · Sentari AI

Building Something From Scratch

Product is 20% building, 80% deciding what not to build.

I led product at an early-stage AI startup as the sole PM — no roadmap, no team, no product. I defined the vision, scaled the team to 10, and shipped from zero to a live App Store launch in six weeks. I built a retention dashboard tracking 2,000+ users, found a 45% onboarding drop-off, and redesigned the flow to cut time-to-activation by 30%. I got addicted to that 80% — the deciding.

V
2025 · DLocal (NASDAQ: DLO)

The Thing I'm Most Proud Of

Nobody asked me to do this.

I built a full institutional-quality equity research report on DLocal — a cross-border payments fintech operating across 40+ emerging markets. A complete 3-statement model. DCF with sensitivity analysis. Comparable company analysis. A contrarian Sell thesis built on structural take-rate compression. Then I published it. It's the clearest proof of how I think: rigorous, independent, and willing to go against consensus when the data says so.

VI
2025 · Independent Build

Friday — My Finance Tutor

I wanted a JARVIS for markets. So I built one.

A voice-first AI finance tutor — talk to it, and it talks back. Real-time speech (Deepgram), reasoning (Claude), live web search, and a heads-up display straight out of a Marvel film. Ask it to walk you through a DCF, explain a yield-curve inversion, or read the macro tape out loud. It's where my engineering, finance, and AI obsessions finally live in one place.

VII
Now · New York

Pointed at Finance

The next chapter is open — and I know which direction it faces.

Recent NYU graduate, based in New York. I'm looking to build my career in the finance industry — Equity Research, FP&A, FinTech Product, or Business Strategy — and open to London (UK High Potential Individual route, no sponsorship needed). If your work lives at the intersection of finance, technology, and emerging markets, we should talk.

The Range

A bigger perspective.

Most people pick a lane. I learned the whole road first — so when I sit at the finance table, I'm not just reading the numbers. I understand the product that made them, the strategy that shaped them, and the story that sells them.

Equity Research Financial Modeling · DCF Valuation FP&A Corporate Finance Business Strategy Product Management Digital Marketing Data Science & AI Python · SQL LLM & Agentic Systems RPA Automation Bloomberg Tableau
The Work

What I've actually done.

i
DLocal · NASDAQ: DLO

Equity Research Report

A contrarian Sell on a NASDAQ-listed fintech, built from scratch. Full 3-statement model, DCF with sensitivity, comparable analysis — and a take-rate compression thesis across 40+ emerging markets.

Read the report → GitHub
ii
Friday · AI Finance Tutor

A JARVIS for Markets

A voice-first AI tutor I built solo — Deepgram speech, Claude reasoning, live web search, and a Marvel-style HUD. Ask it to explain a DCF or read the macro tape, out loud, in real time.

More on GitHub →
iii
Python · Valuation Engine

Automated Financial Modeling

A Python tool that builds integrated 3-statement and DCF models with sensitivity analysis, plus comparable and precedent-transaction analysis — valuation, automated end to end.

View on GitHub →
iv
Python · LSTM · Deep Learning

Yield Curve & Robo-Advisor

An LSTM yield-curve inversion predictor as a recession early-warning signal, paired with a macro-aware portfolio optimizer and a personalized robo-advisor that adjusts allocation by risk profile.

View on GitHub →
v
Forecasting · Strategy

Sales Forecasting & Competitor Analysis

A sunscreen-category demand forecasting and competitive-landscape study — the business-strategy and marketing-analytics side of how I think, not just the model behind it.

View on GitHub →
vi
Koch Business Solutions

Automation at Scale

Rebuilt financial workflows for a global enterprise. 22 products shipped, ~$250K saved a year, 80% fewer failures. No one noticed until it worked.

See the story →
vii
Sentari AI

Product Leadership

Led a team. Shipped from zero to App Store in six weeks. Tracked 2,000+ users and learned what product management actually is — the deciding, not the building.

See the story →
Who I Actually Am

Beyond the résumé.

Prakhar Srivastava
— New York, 2026

I'm obsessed with the big picture. Always have been. I can't look at a company without wanting to model it. Can't have a conversation without wanting to understand the psychology behind it.

Finance is the through-line. I read about behavioral finance, emerging markets, and geopolitics the way other people watch Netflix. I track markets recreationally. I have a personal stake in Robinhood Ventures Fund 1 — not because someone told me to, but because I wanted skin in the game.

But I've never lived in one discipline. I've shipped product, run digital marketing as Director of Marketing for NYU's Graduate Student Council, and think in business strategy by default. That range isn't scatter — it's the reason I see the move two steps before the table does.

I'm genuinely interested in psychology — why people make the decisions they do, at the individual and the systemic level. It's the same question whether you're analyzing a fintech's take rate or a person's risk tolerance.

I use astrology and numerology as frameworks for self-understanding, not superstition. I think there's more signal in ancient pattern-recognition systems than most analytical types admit.

I remember what people say. I notice the small things. I show up. In a world of surface-level networkers, that's rarer than it sounds.

Let's Talk

If you're building at the intersection of finance, technology, and emerging markets — or just want to talk shop — I'd love to connect.

Building my career in finance. New York · open to London. No filler, no "feel free to reach out." Just send the message.

✉ ps5225@stern.nyu.edu in · LinkedIn ⌥ GitHub ↗ DLocal Report workwithprakhar.com