Raghuveer Krishnamurthy, CFA is a data science and financial systems engineer specializing in mathematics-intensive FP&A applications, equipped with an unparalleled blend of expertise in financial analytics, operations research, and intelligent systems. With over a decade of experience spanning financial modeling, applied data science, and applied decision science, Mr. Krishnamurthy today engineers production-grade data science features & solutions at Spindle AI that remove the bottlenecks finance & revenue stakeholders face in answering their most critical analytical questions.

At Spindle AI, Mr. Krishnamurthy combines his rare vantage as an archetypal user, his consulting expertise honed in investment banking, and his formal training in Computer Science and AI to architect and deliver data science tools and solutions for all Spindle AI customers. As a white-glove, forward-deployed counterpart to Spindle’s customers, Mr. Krishnamurthy also spans sales engineering, solving (and engineering solutions for customers to solve) critical data science challenges & finance questions like pricing & packaging, revenue mix shift, margin optimization, GTM alignment modeling, LRP/LTP, capital restructuring, and more.

Mr. Krishnamurthy’s career reflects a progression from building multibillion-dollar financial models at prominent banks and multi-family offices, to retooling Strategic Finance at public enterprises like Twilio (TWLO) and hypergrowth startups like Rippling and CaptivateIQ, to now engineering financial decisioning and data science platforms like those he wishes he’d had earlier in his career. Specializing in Sales & Marketing Finance, Mr. Krishnamurthy recognized how Strategic Finance acts as the connective tissue of an organization, quantifying decisions on portfolio construction, corporate restructuring, and M&A planning.

This vantage now informs his finance data science engineering work, where he builds modules that make such high-stakes analysis faster, more intelligent, more transparent, and systematized. His early experience designing robust internal finance tools using Solver, @Risk, MATLAB, and Python ultimately led him to pursue an M.S. in Computer Science with a specialization in Artificial Intelligence, which he earned from Georgia Tech. He also holds an M.S in Industrial & Operations Engineering from the University of Michigan, where he concentrated on Operations Research, and an M.S. in Management Science & Engineering from Stanford University. 

Before his time in data science and corporate finance, Mr. Krishnamurthy spent seven years in banking and notable multi-family offices, where he built complex financial models for portfolio management, portfolio construction, structured finance, direct investing, and IPO liquidity planning. Mr. Krishnamurthy is a CFA charterholder — among the few equally comfortable writing production data science code as architecting a business unit’s financial strategy.

Outside of work, Mr. Krishnamurthy is an avid sci-fi reader, working through the expansive list of Hugo and Nebula Award-winners and finalists. He sports a deep interest in geopolitics, and makes time each week to stay informed on global affairs. He lives with his wife in beautiful San Francisco, California.  ∎