Quantitative Analyst applicants have rated the interview process at UBS with 3.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 58.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Quantitative Analyst roles take an average of 18 days to get hired, when considering 2 user submitted interviews for this role. To compare, the hiring process at UBS overall takes an average of 29 days.
Common stages of the interview process at UBS as a Quantitative Analyst according to 2 Glassdoor interviews include:
One on one interview: 40%
Phone interview: 40%
Presentation: 20%
Here are the most commonly searched roles for interview reports -
Das Gespraech fand online statt. Es wurden mathematische sowie wirtschaftliche Themen angesprochen. Themen wie machine learning, artificial intelligence, model implementation. Es wurde nicht stark ins Detail eingegangen, sondern eher ein Range an Themen behandelt.
I applied through a recruiter. The process took 1 week. I interviewed at UBS in Jun 2024
Interview
I was really surprised by the attitude of UBS towards the process as well as the candidate's and their own time. After a quick chat with HR, they wanted to sign me up for SIX interviews, over 45 mins each, which sums up to almost 5 hours of meetings for just one recruitment stage. Fortunately, they've agreed to squeeze it to 2.5 hours for the whole process, but having to introduce yourself and go over your CV 4 or 5 times is not necessarily a good use of one's time. The meetings with the team members were very nice and interesting but it was probably the most stretched up recruitment stage I have participated in.
Interview questions [1]
Question 1
Describe briefly your background with emphasis on the most relevant bits to the role
Questions mainly revolved around Derivatives and Risk management, Securities and Portfolio Managements, Credit Risk, Exposures, time series and basic statistics around hypotheses testing, p values , t test , F test , BLUE, regression analysis and python.