Quantitative Research Intern, Summer 2027
Posted Jul 14, 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
Walk me through a time you built a statistical or machine learning model to solve a real problem. What did you choose, and why?
What they are checking: whether the candidate can explain modeling choices and tradeoffs rather than just naming a tool
Tell me about a project where your first approach didn't work. What did you do next?
What they are checking: resilience and whether they iterate methodically instead of guessing randomly
Tell me about a time you had to make a decision quickly with incomplete information. What did you do?
What they are checking: comfort with fast, imperfect decision-making, which mirrors trading conditions
How do you usually decide a research idea isn't worth pursuing further?
What they are checking: judgment about resource allocation and willingness to cut losses on a dead end
What would you do
How would you design a trading strategy using machine learning, starting from a dataset you've never seen before?
What they are checking: whether they understand the full research pipeline: feature selection, backtesting, overfitting risk
Suppose your model shows great backtested performance but keeps losing money live. What would you check first?
What they are checking: awareness of overfitting, look-ahead bias, and regime change as practical failure modes
If you had a market that was moving fast and your model's inputs were suddenly stale or missing, what would you do?
What they are checking: practical judgment about risk management when data quality breaks down
Why options market-making instead of another type of quant work, and what do you think makes markets efficient or inefficient?
What they are checking: genuine interest in the business versus a generic quant interest, and basic market intuition
About the work
Say you flip a biased coin where you don't know the bias, but you get to see 100 flips. How would you estimate the probability of heads, and how confident would you be in that estimate?
What they are checking: grasp of estimation, confidence intervals, and Bayesian versus frequentist thinking
You have two random variables and you're told they're uncorrelated. Are they independent? Explain your reasoning with an example.
What they are checking: depth of probability foundations, not just memorized rules
I'm going to give you a quick math or coding problem and I want you to talk through it out loud as you work. Ready?
What they are checking: speed and accuracy under time pressure, and whether they can think aloud clearly
Explain the bias-variance tradeoff to me like I'm someone outside your field.
What they are checking: communication skill and true understanding versus rote recall
How would you construct a portfolio of strategies to maximize return for a given level of risk, and what would you do differently under constraints like limited capital?
What they are checking: understanding of optimization and portfolio construction basics
Describe a piece of code you wrote in Python that you were proud of. What made it good, beyond the fact that it worked?
What they are checking: coding maturity: readability, efficiency, and whether they think about more than just correctness
Practice this interview out loud.
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Practice this out loudThe full job description
As published by Akuna Capital.