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: see the whole board before the move. Finance is where it all finally points.

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
May 2019 – May 2021 · Navjeevanam Ayurveda Medical Research Institute, Rishikesh

My First Finance Seat

FP&A in the foothills of the Himalayas, where I learned the numbers are never just numbers.

Long before business school, I ran financial planning & analysis for a medical institute in Rishikesh. I built driver-based revenue forecasts across a $240K+ revenue base, modeling patient volume, conversion, repeat visits, and treatment occupancy across consultations, pharmacy, and Panchakarma packages. I ran monthly budget-vs-actual variance analysis on $19K+ monthly streams, and built patient-level unit-economics models across 100+ weekly interactions to find where margin quietly leaked. It was the first time finance truly clicked, and I never looked back.

III
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.

IV
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.

V
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, with no roadmap, no team, and no product yet built. 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.

VI
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.

VII
2025 · Independent Build

Friday, My Finance Tutor

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

A voice-first AI finance tutor that you talk to, 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.

VIII
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, in Equity Research, FP&A, FinTech Product, or Business Strategy, and I'm 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
Certifications

Formally credentialed.

Financial Planning & Analysis Professional (FPAP)

Corporate Finance Institute
Certificate No. 192215173 · Issued August 2026

AI for Finance Specialization

Corporate Finance Institute
Certificate No. 185000950 · Issued June 2026
The Work

What I've actually done.

Corporate Roles
Sentari AI
Product Manager · Founding, Sole PM
2025
  • Defined product vision and owned the roadmap as the sole PM at an early-stage AI startup, with no existing roadmap, team, or product. Scaled the team to 10 and shipped from zero to a live App Store launch in six weeks.
  • Built a retention dashboard tracking 2,000+ users, identified a 45% onboarding drop-off, and redesigned the activation flow to cut time-to-activation by 30%.
Koch Business Solutions
Associate, Automation & Finance Operations
2022 – 2024
  • Redesigned multi-billion-dollar financial workflows using RPA, OCR, and SAP across order-to-cash and procure-to-pay processes.
  • Shipped 22 automation products end to end, saving roughly $250K a year and cutting workflow failures by 80%.
Navjeevanam Ayurveda Medical Research Institute
Financial Planning & Analysis Analyst
May 2019 – May 2021
  • Built driver-based revenue forecasting models across three revenue lines, tracking patient volume and medicine demand as separate drivers. Forecasts ran within 5–10% of actuals under normal conditions, and within 10–15% through the COVID demand surge after re-forecasting with updated volume and consultation-mix assumptions.
  • Ran monthly budget vs. actual variance analysis across revenue lines and cost centers, tracing volume, price, and mix drivers. Corrective recommendations, consumption-based purchasing and selective pricing adjustments, cut avoidable procurement spend ~5–8% in affected categories and improved revenue realization ~3–5%.
  • Served as the sole financial analyst in the administration team, working alongside the staff accountant and coordinating with physicians, pharmacy, and procurement to analyze medicine margins, supplier costs, and treatment utilization for pricing and purchasing decisions.
Independent Projects
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.

ii
Talen Energy · NYSE: TLN

Driver-Based Operating Model & Investment Thesis

A fully sourced, driver-based operating model for Talen's nuclear and gas fleet, built from SEC filings, PJM auction data, and investor disclosures: a monthly revenue and cost build, and an EBITDA bridge tying 3.5x FY2024–FY2026 growth to named drivers. Plus an original thesis on counterparty optionality in a major power purchase agreement, using the contract's own disclosed terms to find a $563M annual gap between headline demand and third-party discount methodology (PJM, Lawrence Berkeley National Laboratory).

iii
Baselayer · Finance & Operations

FY2026 Driver-Based Operating Model

A fully sourced operating model for Baselayer, an AI-powered KYB and fraud prevention platform serving 1 in 5 US financial institutions. Built from public data and industry benchmarks: ARR waterfall, three-scenario analysis (Bear/Base/Bull), working capital, cash forecast, and a KPI dashboard. Bear case grounded in Middesk comp data. Bull case thesis built on Stripe's report that 70% of API calls now originate from AI agents.

View the model →
iv
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 →
v
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 →
vi
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 →
vii
Friday · AI Finance Tutor

A JARVIS for Markets

A voice-first AI tutor I built solo, with 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 →
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, in 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.

Above all, I'm a perpetual student. I treat personal growth like a compounding asset: training the body, sharpening the mind, widening how I see the world. A little better every day, across every dimension.

That's the real through-line. Not finance, not product, not code. The constant underneath all of it is the appetite to keep getting better.

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. Based in New York, open to London. If something here resonated, I'd genuinely like to hear from you.

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