Research Engineer (Options)
Posted Sep 30, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
You'd sit on a systematic options trading team across software design, data engineering, distributed computing and quantitative modeling. Where are you strongest, and where would you need to grow?
What they are checking: Honest self-assessment across a broad role, and whether they know where they would need support.
Tell me about a time you worked closely with researchers or traders who weren't engineers.
What they are checking: Collaboration and translating between research ideas and production-quality code.
What's something technical you've learned recently on your own, and why?
What they are checking: Curiosity and self-driven learning, which suits a role surrounded by new technology.
What would you do
A researcher's code works but is too slow to use on full history. How do you approach speeding it up?
What they are checking: Profiling first and optimizing what matters, while respecting the researcher's intent.
A model result changed overnight and nobody changed the code. How do you investigate?
What they are checking: Systematic debugging that checks data, dependencies and environment when the code itself has not changed.
About the work
How would you design a backtesting system for options strategies that researchers can trust?
What they are checking: Attention to correctness, point-in-time data and options-specific details like expirations and exercise.
Walk me through how you'd distribute a large parameter sweep across many machines.
What they are checking: Practical distributed computing skill, including failure handling and result collection.
How do you compute implied volatility from an option price, and what can go wrong numerically?
What they are checking: Quantitative modeling skill and awareness of edge cases in numerical methods.
How would you store and serve historical options data for fast research queries?
What they are checking: Data engineering judgment for very large, structured options datasets.
What makes research code different from production code, and how do you bridge them?
What they are checking: Understanding of tradeoffs between flexibility and reliability in a research-heavy team.
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As published by DRW.