J'ai postulé en ligne. Le processus a pris 2 semaines. J'ai passé un entretien chez ING en juill. 2022
Entretien
Interview process was vague and open ended. I did recieve some feedback however it was larlgely de-coupled from what the assignment was asking and the implementation provided.
Even though assignment was open ended and mentioned openess to trying out new ideas, based on feedback it seems they had a particular implementation they were looking for and anyhting else would be subpar. For example a specificity on nr of lines on methods that use complex 3rd party libraries vs method cyclomatic complexity which is a more important measure.
Based on statments like "do not limit yourself to what we can come up with" scattered in the file they provided, this clealry creates a decoupling from expectations vs how it will be assessed. It seems that what they were actually looking for was a fully productionalisable bug-free solution (24+ work hrs) to an interview assessment which is an unrealistic expectation.
Did I also mention the cancelling of the code review session (which gives candidates chance to explain thought process, approach etc.) 5 minutes before scheduled start time which shows a lack of professionalism and disregard for candidates. I guess one of the code reviewer's LinkedIn profile which shows "soft skill:restless" was the main deciding factor.
There's nothing wrong with setting a clear, precise expectations in assessments for candidates as long as they are made clear if that's what the company is looking for. It is my opinion that if an assignment is left open-ended then it should be treated like that.
Questions d'entretien [1]
Question 1
Open ended assignment with free choice of technology but seemingly penalised for trying out new ideas.
J'ai postulé via la recommandation d'un employé. Le processus a pris 3 mois. J'ai passé un entretien chez ING (Amsterdam) en déc. 2017
Entretien
Procedure:
* Home assignment similar to IQ tests, plus some interpersonal/behavioural questionnaire
* Interview with the hiring manager(s) and/or future peers, ie, Chapter Lead Data Analytics/Science, in order to get a broad assessment, plus to see whether there is a good cultural fit.
The Chapter Lead people are generally nice and welcoming, with standard questions, well described on many other interview reviews on Glassdoor.
* Interview with team members, ie, data scientists/analysts. They present themselves, ask you to present yourselves, and half of the time is devoted to a business use case.
* Interview with another Chapter Lead peer, to assess interpersonal skills
Questions d'entretien [2]
Question 1
The use case was a dumb one: forecasting of the future operations, in the retail bank application, with the very same accuracy as the historical operations (for instance, the application should forecast that you will buy some cake at Albert Heijn in ten days from now, on a Tuesday morning at 10:12, for an amount of 1.27 Euros). When I tried to transform the use case so that it makes more sense business-wise (for instance, a budget planning exercise, where we still keep the analysis of time series), the interviews were dumb and wanted to stick to the original formulation of the use case.
They asked very specific questions on ML algorithms (eg, give me the three drawbacks of the PCA algorithm), without being interested in my capacity to see the bigger picture (for instance, how to put PCA in the perspective of dimensionality reduction, and how it compares to other algorithms for that purpose).