Quantitative Development & Strategy Intern, Summer 2027
Posted Aug 5, 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 time you found a bug in someone else's code, or someone found one in yours. What did you do next?
What they are checking: 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?
What they are checking: 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?
What they are checking: 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?
What they are checking: self-awareness and error-checking habits, since fast and accurate problem solving is called out as essential to the role
What would you do
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.
What they are checking: 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?
What they are checking: 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?
What they are checking: judgment about risk and communication style when working in a live, high-stakes system
About the work
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?
What they are checking: 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?
What they are checking: 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.
What they are checking: 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.
What they are checking: 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?
What they are checking: 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?
What they are checking: depth of computer science fundamentals beyond just scripting in Python
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As published by Akuna Capital.