What to expect interviewing for a quantitative analyst role at Munich Re: a psychometric test, a Teams interview with an actuary and HR, an assessment center, and a final technical interview, plus related analyst reports.
$111K
Avg. Base Comp
$138K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
The one report that names the Quantitative Analyst role describes a multi-stage process: CV and cover letter screening, an online psychometric aptitude test, a Teams interview with an actuary and an HR representative, an assessment center, and a final presentation plus technical interview. That candidate found the video interview friendly and not overly technical, with a Fermi estimation question about lightbulbs in London and STAR-style behavioral questions. The assessment center centered on a timed group case study about a supermarket chain, followed by an employee Q&A and a spaghetti-and-marshmallow tower exercise. The candidate was rejected about a week later by phone and received detailed feedback.
Reports from neighboring analytical roles at Munich Re point in a similar direction, though they are different jobs. An actuarial intern described another estimation question (balloons filling a room) and questions on machine learning and statistical modeling. An actuarial analyst reported a SQL question on how GROUP BY and WHERE differ in execution order, plus a two-part underwriting case. An actuarial intern who received an offer was asked how shocking assumptions moves reserves. A financial analyst was opened with a question about past actuarial experience.
In practice, rehearse thinking aloud on estimation problems, keep two or three concrete work examples ready, and review basic SQL and statistics mechanics. Because the Quantitative Analyst evidence comes from a single candidate, treat the exact stages as a guide rather than a fixed sequence.
Synthesized from 6 candidate reports by our editorial team.
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Real interview reports from people who went through the Munich Re (Group) process.
I came into the interview process at Munich Re having taken the ASNA exam, which seemed to be a pretty clear signal they were looking for. The whole thing moved surprisingly fast — from initial screening to the final decision took less than three weeks. The first round was a digital application, followed by a screening call where I fielded standard behavioral questions: why I applied, what I was proud of, and why Munich Re specifically. The interviewers wanted to understand my background and what drew me to the role, so having a clear story about my actuarial interests and career trajectory helped. After that screening cleared, I had a 30-minute in-person interview scheduled. I walked in and it started almost immediately — no small talk, just straight into it. An HR person and an actuarial analyst sat down with me. The conversation covered my resume, past experiences, and technical foundation. They asked about machine learning, statistical modeling, and software engineering concepts, which caught me off guard initially. They were thorough but genuinely interested in my reasoning, and when I asked them questions about the team and their work, they gave insightful answers rather than deflecting. There was also a somewhat unusual question thrown in — something like a Fermi estimation about how many balloons you'd need to fill a room. It tested how I think through problems, not whether I knew a specific formula. The whole interview wrapped up in about 25 minutes, giving me time to ask questions back. What stood out was that regardless of the outcome, it felt like a learning opportunity. The interviewers weren't just checking boxes; they seemed genuinely interested in whether we'd be a good fit for the team. The process was fast-paced but not stressful, and the whole experience from application to decision was streamlined.
Prep tip from this candidate
Practice Fermi estimation and dimensional analysis problems before your interviews — Munich Re uses these to test problem-solving approach rather than memorized knowledge. Also have a crisp answer ready for why you're applying and what specific skills in statistical modeling or machine learning you want to develop, since they probe technical depth alongside behavioral fit.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Munich Re (Group)
Which model would perform better and why?
| Question | |
|---|---|
| Random Forest Explanation | |
| Same Characters | |
| Data Cleaning Experiences | |
| Random Forest Expansion | |
| 2nd Highest Salary | |
| Employee Salaries | |
| Bagging vs Boosting | |
| Hurdles In Data Projects | |
| Random SQL Sample | |
| Scalped Ticket | |
| P-value to a Layman | |
| Size of Joins | |
| Missing Housing Data | |
| Assumptions of Linear Regression | |
| Success Measurement | |
| Target Indices | |
| Possibly Biased Coin | |
| Data Preparation for Imbalanced Data | |
| HHT or HTT | |
| Lasso vs Ridge | |
| Duplicate Rows | |
| Type-ahead Search | |
| Cyclic Detection | |
| Three Zebras | |
| Precision and Recall | |
| Xgboost vs Random Forest | |
| SARIMA in Retail Forecasting | |
| Integer String Addition | |
| Overfit Avoidance |
Synthesized from candidate reports. Individual experiences may vary.
The candidate who named the Quantitative Analyst role reports a CV and cover letter screen followed by an online psychometric aptitude test. Other analyst candidates describe digital applications and short screening calls, so expect an early filter before any live interview. Details of the test content were not reported.
The Quantitative Analyst candidate describes a friendly Teams interview with an actuary and an HR representative. Questions were not very technical: a Fermi estimation problem about lightbulbs in London and STAR behavioral questions. A candidate for an adjacent actuarial role also reported an estimation question, so practice explaining your reasoning rather than aiming for a precise number.
The same candidate reports a timed group case study about a supermarket chain, with issues such as trolley theft, gluten-free stock and car park capacity. An informal Q&A with recent hires and a spaghetti-and-marshmallow tower exercise followed. These may feel unrelated to quantitative work, so candidates should stay composed and communicate clearly. This stage is reported by one candidate only.
The final stage in that report combined a presentation about the candidate and a technical interview that stayed fairly broad rather than deeply analytical. Adjacent analyst candidates report SQL mechanics, reserve-assumption questions and underwriting-style cases, which may indicate topics to review. Outcome feedback in the Quantitative Analyst report arrived by phone about a week later.
