Quantitative Trading Strategist - Equity 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
Tell me about a model you took from research into live trading. What surprised you once it was live?
What they are checking: Real experience deploying strategy changes and learning from the gap between test and production.
What structural improvements have you found by analyzing large trading datasets?
What they are checking: Whether they find platform-wide wins, which the posting says matter more than single-seat gains.
What would you do
A strategy change improves P&L in testing but increases risk during fast markets. How do you decide whether to ship it?
What they are checking: Whether they balance pricing, execution and risk instead of chasing one number.
A trader says the system is quoting badly in a group of names, but your data says it's fine. What do you do?
What they are checking: Whether they take trader insight seriously and dig deeper instead of trusting aggregate stats.
How do you work with engineers when your strategy idea needs a change to production systems?
What they are checking: Collaboration in a non-siloed setup where research, trading and engineering iterate together.
About the work
How would you measure whether a change to our quoting logic improved pricing quality across thousands of underlyings?
What they are checking: Whether they can design fair evaluation for changes that affect a broad universe, not one name.
Walk me through how you'd study adverse selection in our fills and what you'd change if it was high.
What they are checking: Understanding of market-making economics and how to turn fill analysis into strategy changes.
How would you design an A/B test for a quoting change when market conditions keep shifting?
What they are checking: Statistical rigor in live experiments where randomness and regime changes can mislead.
How do you manage aggregate risk like delta and vega across a systematic options book?
What they are checking: Understanding of portfolio-level risk management in a large automated platform.
How do you keep live trading logic robust when an input like a reference price goes stale?
What they are checking: Their attention to system robustness and safe behavior when data fails.
How do you price options on a name with an upcoming event and very little trading history?
What they are checking: Practical pricing judgment when data is thin and the model needs help.
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Practice this out loudThe full job description
As published by IMC Trading.