XTX Markets Interview Questions
A representative XTX Markets quant-interview practice set — machine learning, linear algebra and regression — matched to how the firm interviews, each with a full worked solution.
Inside the XTX Markets interview
XTX Markets is a London-based algorithmic market maker that trades FX and equities almost entirely on the strength of its statistical models. Its interviews are unusually research-heavy, probing machine learning, regression, linear algebra, statistics, and optimization alongside clean, performant coding.
What they test
The center of gravity is statistical learning: machine learning (clustering, kernels, ensembles, PCA, EM) and regression (OLS, ridge, lasso, logistic), backed by a deep linear-algebra core around covariance matrices, the SVD, and eigenstructure. Around that sit statistics (MLE, sampling, multiple testing) and a layer of numerical optimization and coding.
The recurring shapes
Expect to derive estimators from first principles (the OLS normal equations, why we divide by n−1, the first principal component) and to reason about shrinkage and the bias–variance tradeoff in ridge and lasso. A second thread is matrix structure — PSD covariance, low-rank approximation via SVD, QR via Householder — and a third is turning models into convex optimization: gradient descent, KKT conditions, mean–variance portfolios.
How to approach
Be fluent moving between the geometry, the algebra, and the code: state the objective, write its gradient or normal equation, and then implement it cleanly and numerically stably (log-sum-exp, quickselect, median-of-two-sorted-arrays). Name your modeling assumptions out loud — independence, stationarity, multiple-testing inflation — because XTX cares as much about why a method works as about getting the answer.
The mix leans medium, with a substantial hard tier in linear algebra, optimization, and statistics and a couple of easy warmups to anchor the fundamentals.
XTX Markets machine learning questions (6)
XTX Markets linear algebra questions (4)
XTX Markets regression questions (4)
XTX Markets statistics questions (4)
XTX Markets coding questions (3)
XTX Markets optimization questions (3)
XTX Markets interview FAQ
What kind of questions does XTX Markets ask in quant interviews?
Candidates most often report machine learning, linear algebra and regression questions. This page collects 24 of them — each with a full worked solution.
How hard are XTX Markets interview questions?
The set spans 2 easy, 15 medium and 7 hard problems. Most sit at medium difficulty — solvable in a few minutes with clean reasoning — with a harder tail that rewards knowing the canonical tricks.
How do I prepare for the XTX Markets quant interview?
Work through this set by topic (use the sidebar), starting from your weakest area. 6 problems are free to open with their full solution, so you can judge the quality before anything else. Then broaden out with the related firms below — the question families overlap heavily.
Are these the actual XTX Markets interview questions?
This is a representative practice set matched to how XTX Markets interviews — chosen from our bank by topic and style rather than claimed as verbatim reports. Every problem carries a full worked solution.