intercontinental exchange·Data Scientist·Technical Phone Screen
May 2026
Technical phone screen for a Data Scientist role at ICE, heavy on quantitative finance. The whole thing centered on implied volatility and Black-Scholes, which I wasn't expecting to go that deep on for a data science position.
- Explain how Newton-Raphson works for finding implied volatility, and walk through the specific conditions where it breaks down, including issues with the objective function, its derivative, step sizes, and edge cases.
- How would you choose the initial volatility seed before running Newton-Raphson for implied vol, and what heuristics or real data would you lean on to justify that choice?
- Write out the closed-form Vega formula for a European option under Black-Scholes, define every variable with units, and explain how Vega's size affects the step size in Newton-Raphson updates.
“I knew the basic mechanics but stumbled when they pushed on failure modes.” The rest of the author's notes on Data Scientist interview at intercontinental exchange, Technical Phone Screen round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.
View Post