Qube Research & Technologies (QRT) hires Quant Researcher and Quant Developer. Candidates report 3 interview stages. Below: what each round tests and how to prepare, the timeline, pay and a 4-week prep plan, drawn from candidate reports and QRT's own recruiting pages.
Qube Research & Technologies interview: quick answer
- Stages3
- Online assessmentHackerRank · algorithmic coding · candidate-reported
- TimelineApplications are reviewed on a rolling basis.
- Final roundFinal / Onsite: Candidate-reported · deeper technical + fit
- Pay (candidate-reported)Quant Researcher, New grad (MS/PhD): candidate-reported (USD-equivalent) total comp
- RolesQuant Researcher, Quant Developer
Preparing for Qube Research & Technologies? Work the rounds in order in the free Qube Research & Technologies interview funnel.
The QRT interview process at a glance
| # | Round | Format and length | Prep |
|---|---|---|---|
| 1 | Online Assessment | HackerRank · algorithmic coding · candidate-reported | Practice |
| 2 | Technical Interview | Coding + probability/statistics · candidate-reported | GuidePractice |
| 3 | Final / Onsite | Candidate-reported · deeper technical + fit | GuidePractice |
Stages are listed in the order candidates report them. Formats come from candidate reports and change between cycles, offices and teams; not every candidate sees every stage.
Every QRT round: what it tests and how to prepare
1Online Assessment
A HackerRank-style algorithmic OA that gates the process. Candidate-reported problems are trading-flavored: a trading-platform event log returning net profit at each QUERY (Σ position × cumulative price change), a minimum-cost array-reduction (Huffman-style min-heap greedy, O(n log n)), and a longest-substring-with-at-most-k-restricted-characters sliding window. Auto-graded: clean, correct, efficient code gates progress.
Question types: mostly coding, especially arrays, greedy, heap and prefix sum. Latest candidate report for this round: Jul 2026.
How to prepare
- Read the value-class definition carefully (the source had a comment/code mismatch on which value is restricted).
- For the event log, keep two dicts — positions per ticker and cumulative price change per ticker — and compute the sum only at QUERY. O(1) per non-query event.
- Handle edge cases and large n (up to 1e5). Watch integer overflow and empty inputs.
Watch out: Don't reach for DP.
2Technical Interview
Coding (DS/algos): design and justify a matrix class; two missing numbers in 1..k+2; fewest moves-to-back keeping prefix sums nonnegative; single-edit string transforms. Quant probability/stats: XOR of a fair and a two-headed coin; P(sum of 100 dice > 400) via CLT; correlated standard normals (Corr 0.5): P(X > 3Y), P(X > 3Y | X > 0).
- Two to five interviews of about 45 minutes with junior then senior researchers on regression, ML, probability and your CV.
- Reported ML theory includes random forests and their variance, random forest versus XGBoost, ridge and lasso, and positive semidefinite matrices.
- Known question types: the product of the two regression slopes (y on x and x on y) and counting trading paths from flat to a given position.
Question types: mostly coding, probability and expectation, especially arrays, bit manipulation, conditional probability and discrete probability. Latest candidate report for this round: Jul 2026.
How to prepare
- Correlated normals: write Y = ρX + √(1−ρ²)Z. P(X > 3Y) reduces to a linear combination of independent normals being positive — compute the sign probability via the resulting normal's mean/variance; the conditioning on X > 0 is a bivariate-normal quadrant argument.
- P(sum of 100 dice > 400): mean 350, variance 100·; standardize and use the normal tail. Know the numbers cold.
- Prefix-sum-nonnegative: greedily move the most-negative-contributing elements to the back — reason about why a heap of the smallest prefix contributors is optimal.
Full Technical Interview guide →Practice this round (11 questions) →
3Final / Onsite
A closing onsite that goes deeper on algorithms, modeling, and fit, and checks that you can work in an engineering-heavy research org. Candidate-reported specifics are limited; be ready to extend any earlier problem and to talk through a project end-to-end.
- Some teams add a machine-learning project of about two weeks, which you then defend.
How to prepare
- Be ready for follow-up depth — QRT interviewers push a working solution toward optimization and edge cases.
- Bring a project you can defend technically, from data and design choices through validation.
Practice the QRT rounds in order
Each round in the QRT funnel has its own practice set, with worked solutions and progress tracking. A free account saves your progress across rounds.
Timeline
Applications are reviewed on a rolling basis. Most processes take about three to five weeks, though reports range from two weeks to three months, and silence after late rounds is common.
Intern vs full-time
For 2027, QRT lists quantitative research and trading internships of four to six months across Aarhus, Budapest, Dubai, Geneva, London, Paris and Zurich, plus Asia programmes, software and quant developer roles, and a PhD and postdoc track. Penultimate and final-year bachelor's students are eligible for research internships.
A 4-week QRT prep plan
Built from the order of Qube Research & Technologies's rounds and the topics in each round's practice set. Compress it if your first interview is sooner.
| When | Focus | What to do |
|---|---|---|
| Week 1 | Foundations | Review coding, probability and expectation, the topics that dominate Qube Research & Technologies's practice sets. Start with Quant coding course and Probability course. Work the easy and medium questions in the Qube Research & Technologies question set. |
| Week 2 | Early rounds: Online Assessment and Technical Interview | Practice coding, probability and expectation under time pressure. Talk every answer through out loud; interviewers score the reasoning. |
| Week 3 | Later rounds: Final / Onsite | Move to the harder final-round topics. Do timed coding sessions in your interview language. Read how quant superdays work. |
| Week 4 | Rehearse the full loop | Run each practice round in order, redo the questions you missed, and prepare two project stories plus a specific answer to "why Qube Research & Technologies?" (see behavioral questions at trading firms). |
QRT pay
| Role | Level | Total comp | Notes |
|---|---|---|---|
| Quant Researcher | New grad (MS/PhD) | candidate-reported (USD-equivalent) | Base + bonus; strong for a London quant seat. Verify against a recent offer. |
| Quant Developer | New grad | candidate-reported (USD-equivalent) | Engineering ladder; bonus tracks firm and team performance. |
Total compensation means base salary plus bonus and any sign-on, as candidates self-report it. Job postings usually show base salary only, so posted figures and outside salary pages often look lower. Rough ranges only, NOT offers. QRT does not publish comp; London quant comp varies widely by team and level. Candidate-reported and directional. Source: Candidate self-reports / public aggregators (levels.fyi, Glassdoor) — not employer-verified. Last updated July 17, 2026.
QRT teams and what their interviews test
QRT hires researchers and engineers to build systematic strategies and the platform behind them. The tracks share a coding-heavy OA and then weight toward research (probability/stats/modeling) or engineering (algorithms/systems).
| Tracks | What it does | What its interviews test |
|---|---|---|
| Quant Researcher Quant Researcher | Research and validate systematic signals and models across asset classes. | HackerRank OA → probability & statistics (correlated normals, dice-sum tails, estimation) + coding → research reasoning. |
| Quant Developer / SWE Quant Developer | Build the research and trading platform — data structures, performance, reliability. | HackerRank OA → algorithms & data-structure design (matrix class, string transforms, heap problems) → systems discussion. |
About QRT
| Firm type | Systematic / quantitative investment manager |
|---|---|
| Trading style | Technology- and data-driven systematic · Multi-asset systematic (mid frequency) |
| Founded | 2018 |
| Headquarters | London, UK |
| Other offices | Paris, Geneva, Hong Kong, Singapore, Mumbai, Dubai |
| AUM | ~US$38B (2026, reported) |
| Employees | 2,000+ globally (2026, reported) |
| Reported performance | Not disclosed |
| Typical length | About 3 to 5 weeks, ranging from 2 weeks to 3 months |
| Interviews after the test | 2 to 5, depending on the team |
Spun out of Credit Suisse in 2018
QRT was founded in 2018 when its systematic/quantitative team spun out of Credit Suisse, led by Pierre-Yves Morlat and Laurent Laizet. Headquartered in London, it has grown quickly into one of Europe's larger quant managers, running technology- and data-driven strategies across asset classes with offices in several financial hubs.
Culture
Engineering- and research-heavy, technology-first. Fast-growing since the 2018 spin-out from Credit Suisse; teams build systematic strategies across asset classes with a strong software and data-infrastructure backbone.
What the interviews feel like
Coding-forward. A HackerRank algorithmic OA gates the process, and interviews mix clean data-structure/algorithms work with probability & statistics reasoning. They want correct, efficient code and a candidate who can also reason about randomness and estimation.
Practice for QRT on QuantVault
Practice
Courses
Further reading
- How quant superdays work
- Behavioral questions at trading firms
- Market-making game interview guide
- The quant interview process, explained
Similar firms to compare
Firms with a similar business and interview style. Many candidates interview at several of them in the same cycle.
Sources and how this guide is built
- Updated October 20, 2026; firm data last reviewed July 17, 2026; pay last updated July 17, 2026.
- Round detail draws on 11 questions candidates report from Qube Research & Technologies interviews (the most recent report across all rounds is from Jul 2026). A separate curated QRT question set of 24 problems collects the most useful practice for this firm.
- Qube Research & Technologies's own pages: QRT careers.
- Public candidate reports and outside interview guides are cross-checked against each other. Where they disagree the page says "reports differ"; details from a single source are marked as candidate reports.
- No actual interview questions are reproduced on this page. The questions, with worked solutions, are in the practice rounds.
QRT interview FAQ
How long does the Qube Research & Technologies interview process take?
Applications are reviewed on a rolling basis.
What happens in the Qube Research & Technologies final round?
Final / Onsite (Candidate-reported · deeper technical + fit). A closing onsite that goes deeper on algorithms, modeling, and fit, and checks that you can work in an engineering-heavy research org. Candidate-reported specifics are limited; be ready to extend any earlier problem and to talk through a project end-to-end.
How much does Qube Research & Technologies pay?
Candidate-reported total compensation: Quant Researcher (New grad (MS/PhD)) candidate-reported (USD-equivalent); Quant Developer (New grad) candidate-reported (USD-equivalent). These are self-reported totals including bonus, not offers; job postings usually list base salary only.
How should I prepare for the Qube Research & Technologies interview?
Prepare round by round over about four weeks: foundations first, then the early rounds (Online Assessment, Technical Interview, Final / Onsite), then the later rounds, then a full rehearsal. Each round has its own practice set on QuantVault.
What does Qube Research & Technologies do?
Qube Research & Technologies (QRT) is a systematic / quantitative investment manager headquartered in London, UK. QRT was founded in 2018 when its systematic/quantitative team spun out of Credit Suisse, led by Pierre-Yves Morlat and Laurent Laizet.
Is there a market-making game at QRT?
No. None is reported.
Can undergraduates apply for quant research at QRT?
Yes. Penultimate and final-year bachelor's students are eligible.
What is the QRT data challenge?
QRT runs a task on the ENS Challenge Data platform; the 2026 task, on forecasting asset-allocation performance, opened on 22 January 2026. Strong results can lead to follow-up from the firm.
How many interviews are there at QRT?
Two to five after the test, depending on the team.
Can I apply to several QRT offices?
You apply to one location, with a short written motivation answer, and are matched to a team during the process.
Does everyone take the QRT online test?
No. Some candidates skip it, so prepare interview material from the start.
Start preparing for Qube Research & Technologies
Open the interactive Qube Research & Technologies interview funnel: every stage with its practice set, from the first screen to the final round. Create a free account to save your progress.