Quantitative Development & Strategy Intern, Summer 2027
Posted Aug 5, 2026 · We last checked this listing on Sep 20, 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.
Behavioral
Tell me about a time you found a bug in someone else's code, or someone found one in yours. What did you do next?
how the candidate handles code review and accountability in a collaborative codebase
Describe a time you had to learn a new technical concept very quickly to finish something. How did you go about it?
speed and independence of learning, since the internship expects fast ramp-up on markets and internal systems
Tell me about a time you disagreed with a teammate or teacher about the right technical approach. What happened?
how the candidate collaborates with researchers, traders, and engineers who may have different priorities
What's a math or coding problem you got wrong at first, and how did you catch your mistake?
self-awareness and error-checking habits, since fast and accurate problem solving is called out as essential to the role
Technical
Walk me through a project where you wrote object-oriented Python code from scratch. What classes did you design and why did you split things up that way?
whether the candidate actually understands OOP design choices rather than just using classes because they were told to
Say you have a large array of price ticks and you need to compute a rolling statistic over it fast. How would you approach that in Python, and where would performance likely break down?
comfort with numerical computing and awareness of Python's performance limitations, since production trading code needs speed
Explain how you'd price a simple option using a basic model, and what assumptions that model relies on.
baseline grasp of derivatives pricing concepts expected for a quant strategy role
Give me a linear algebra concept you've used outside of a classroom setting. What was the problem and how did the concept actually help you solve it.
whether math knowledge is applied and internalized versus memorized for exams
Tell me about a project where you had to optimize code that was too slow. What did you profile, and what actually fixed it?
real experience with performance optimization versus theoretical knowledge of it
How would you explain the difference between a stack and a heap, or how memory is managed in a language you know well?
depth of computer science fundamentals beyond just scripting in Python
Situational
Suppose a trading strategy you're maintaining starts behaving oddly right as the market is moving fast. Walk me through how you'd figure out what's wrong.
ability to debug calmly and methodically under time pressure, which matters a lot in live trading systems
If you had a dataset of historical trades and wanted to find a signal that predicts short-term price movement, how would you start? What would make you trust or distrust a result?
statistical reasoning and skepticism about overfitting or spurious correlations
Imagine you propose a change to an existing piece of production trading code and a senior engineer pushes back, saying it's too risky right before expiration. What do you do?
judgment about risk and communication style when working in a live, high-stakes system
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