Hi, I’m Pranathi!
I am a finance and computing enthusiast,
I’ve built my career at the intersection of finance, data, and technology, working across venture capital, private equity, fintech, and research. Along the way, I’ve had the chance to work with fast-growing startups, established financial institutions, and cutting-edge academic projects. Now, I’m excited to keep pushing that intersection forward by building, learning, and creating impact in the spaces where strategy and innovation meet.
Current Work
Quantum Computing Research | Georgia Tech
I’m part of a research team using quantum algorithms to make financial simulations faster and smarter. My work has centered on applying Grover’s algorithm to risk modeling, finding ways to cut simulation time significantly while keeping accuracy high. What excites me most is seeing how concepts that once felt futuristic are already changing how we think about fraud detection and resilient financial systems.
Previous Work
Venture Capital | Capital Partners (NYC)
My time in VC is a crash course in spotting what makes a startup tick. I research fintech and SaaS startups, mapped competitors, sized markets, and built models to see which opportunities were worth chasing. On the portfolio side, I design KPI dashboards that give founders sharper visibility into performance and surfaced growth opportunities. It’s my front-row seat to early-stage investing, where data and founder instincts collide.
Private Equity | Capital Partners (NYC)
Private equity was my first deep dive into deal-making. I built cash flow and LBO models for $150M+ buyouts, stress-tested assumptions, and pulled it all together in investment memos for partners. It was intense, detail-driven work that sharpened my technical foundation and taught me how to turn complex numbers into clear insights for high-stakes decisions.
Strategy & Research | EarnIn (Bay Area FinTech)
I worked on projects at the intersection of product, data, and finance. I built frameworks to evaluate how new features would impact customer adoption and retention, and partnered with product managers to test different pricing models. A big part of my role was translating data into clear, actionable insights, everything from SQL-driven dashboards to slide decks for leadership.
Credit Risk | American Express (NYC)
I joined the risk team, where I worked on analyzing a $10B+ credit portfolio, building regression models to forecast delinquency trends. I also automated dashboards that cut reporting time and flagged early risks, a few of which were later built into policy updates. It was my first time seeing how technical analysis can ripple into real-world strategy at a global scale.
Data Science & Analytics | Splash BI
My first real exposure to data + finance. I built interactive dashboards that consolidated client financials, streamlined reporting cycles, and ran SQL variance analyses that uncovered lost revenue. It’s where I realized I genuinely enjoy taking messy datasets and turning them into stories people can actually use.
👩🏻💻 Founder | Startup
A fresh take on startup finance. Velvet Ledger makes finance simple, intuitive, and founder-friendly. Instead of drowning in spreadsheets, teams get clean tools to track burn, forecast runway, and share dashboards investors actually want to see. The goal is straightforward: bring CFO-level clarity to founders who’d rather spend their energy building.