Barclays quantitative analyst candidates report interviews built around probability, statistics, stochastic modelling and coding, plus questions on Barclays values. Formats vary by team and level, from a single superday to multi-stage assessment centres.
$143K
Avg. Base Comp
$193K
Avg. Total Comp
3-5 rounds
Typical Rounds
Not reported
Process Length
Barclays quantitative analyst interviews, as candidates describe them, centre on probability, statistics and stochastic modelling, with coding and Barclays values questions running alongside. The mix changes by team and level, so treat the reports as a range of possibilities rather than one fixed loop.
The most detailed offer report describes a full day: an HR screen and coding assessment, a call with a trader, then four superday rounds. Three were quantitative, covering probability, stochastic processes, statistics and linear algebra through a mix of discussion and paper problems, and one was behavioral. Another candidate met several interviewers who kept returning to OLS assumptions, order statistics and basic probability. A 45-minute phone screen for a quantitative finance role covered geometric and normal distributions and stochastic modelling.
Other reports lean toward derivatives or programming. One candidate described roughly half coding and data structures and half finance, statistics and maths, including options pricing, PCA, multicollinearity and Bayes' theorem. A graduate quant candidate reported four LeetCode-medium problems and a data-breach case study. A 2026 report involved deriving geometric Brownian motion, working through Itô's lemma and defending code from an earlier HackerRank test. A counterparty credit risk quant panel was meant to cover exposure metrics such as PFE and EEPE.
Expect to explain your reasoning aloud rather than only reach answers, and to say why Barclays and how its values show up in your work. Feedback timing is a pain point: one candidate waited about a month after an assessment centre. Most candidates did not receive an offer, though one reported an offer and another declined one.
Synthesized from 20 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the Barclays process.
The interview process was intense and multifaceted. I started with a three-hour HackerRank test as part of an in-person assessment centre, which set the tone for what would be a demanding day. After that came a math and statistics interview where they dug deep into probability and stats concepts. The stochastic calculus interview was particularly tough — I had to derive the Geometric Brownian Motion and work through Itô's lemma and risk-free pricing models. They really wanted to see if I could handle the mathematical rigor expected of a quant.
What caught me off guard was the programming interview that followed. We went through the HackerRank test I'd done earlier, and they had me walk through my approach, then asked me to improve my solutions. They weren't just looking for code that worked; they wanted to see how I'd optimize and refactor under pressure. Throughout the day, there were also random mental math curveballs — like being asked to multiply 342 by 54 in ten seconds while discussing something else entirely. It felt designed to test how you handle pressure and quick thinking outside of a structured problem.
The behavioural round wrapped things up, covering standard ground like why Barclays, why S&T, and how I work with others. By the end of the day I was exhausted, but the process gave them a pretty complete picture of both technical depth and resilience. The combination of probability, machine learning, deep learning basics, and core calculus meant they weren't interested in just one skill — they wanted someone who could move fluidly across the quant toolkit.
Prep tip from this candidate
Deep focus on stochastic calculus — specifically deriving GBM, Itô's lemma, and risk-free pricing — is critical. Also practice mental arithmetic under pressure and be ready to defend and improve your code in a code review setting, not just write it. The day is long and deliberately stressful, so mock the full assessment centre experience if you can.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Barclays
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Bagging vs Boosting | |
| Compute Variance | |
| Attribution Rules | |
| Find the Missing Number | |
| Priority Queue Using Linked List | |
| Sort Strings | |
| CNNs vs Intensity-Based Features | |
| Data Preparation for Imbalanced Data | |
| Overfit Avoidance | |
| Prime Numbers Identification | |
| Blob Indexing | |
| Impossibly Iterative Fibonacci | |
| Safe Deployments | |
| Bias vs. Variance Tradeoff | |
| String Palindromes | |
| Justify a Neural Network | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| Dropbox Database | |
| Empty Neighborhoods | |
| Rolling Bank Transactions | |
| 500 Cards | |
| Maximum Profit | |
| Employee Salaries | |
| Merge Sorted Lists | |
| Subscription Overlap | |
| Comments Histogram | |
| Top 5 Turnover Risk | |
| Closest SAT Scores |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report timed online tests before any live interview. These include numerical or data-interpretation reasoning, a situational judgment test tied to Barclays values and a personality questionnaire. Some candidates also describe a coding assessment, such as Codility, or a three-hour HackerRank test held at an in-person assessment centre. The mix likely depends on the team and whether the role is early-career or experienced.
Early live conversations are reported to vary. One candidate had an HR screen followed by a call with a current trader about their background. Another had a screening call that went straight into OLS regression assumptions. A third had a 45-minute quantitative phone interview on geometric and normal distributions and stochastic modelling. Expect a mix of motivation questions and a first technical probe, though the balance may differ by team.
This is the heaviest part of the reports. Candidates describe probability, order statistics, stochastic processes, linear algebra, regression diagnostics, PCA, multicollinearity and Bayes' theorem. Several were asked to work problems on paper or explain their reasoning verbally. Finance-flavoured versions covered options pricing, delta and stochastic volatility, and one 2026 report involved deriving geometric Brownian motion and Itô's lemma. A credit risk quant panel was reportedly meant to cover CCR and exposure metrics.
Coding appears in different forms depending on the report. One candidate had interviews split roughly 50/50 between coding and data structures and finance and maths, including Python data structures. Another had four LeetCode-medium problems, and a 2026 report had the candidate walk through and improve their earlier HackerRank solutions. One graduate quant process also included a data-breach case study presented as if to senior stakeholders. Several candidates were asked about their coding background and preferred languages.
Behavioral rounds typically ask why Barclays, why the role, what challenges you have handled and how you work with others. Candidates say the interviewers care about Barclays values, and one described a conversation about why they wanted to move roles and what they wanted next. Communication after the interviews is a common complaint. One candidate waited about a month after an assessment centre, then received a rejection with feedback over Zoom.
