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      Entretien pour Data Science Consultant

      19 mars 2023
      Candidat à l'entretien anonyme
      Londres, Angleterre

      Autres retours d’entretien d’embauche pour un poste comme Data Science Consultant chez Capgemini

      Entretien pour Consultant Data Scientist

      22 mars 2022
      Candidat à l'entretien anonyme
      Aucune offre
      Expérience neutre
      Entretien moyen
      Aucune offre
      Expérience négative
      Entretien difficile

      Candidature

      J'ai postulé en ligne. Le processus a pris 3 semaines. J'ai passé un entretien chez Capgemini (Londres, Angleterre) en févr. 2023

      Entretien

      First Stage (2 hours): 1 - 2 -1 interview & Modelling Exercise. firstly they sent me a modelling project an hour before the interview begins involving taking a dataset with 20+ features and preprocessing, modelling and visualising the results. The interview then commences with roughly half the time spent on follow up questions about the project and another half about general work experience. This stage generally went smoothly as the focus is more on your reaction to thinking under heavy time pressure, rather than on delivery. Second stage (3 hours): Talent Selection Assessment. This stage involves an hour of working within a group of people applying for various roles. You're expected to take a business case and come up with a strategy, then write out a powerpoint describing your approach. You then spend half an hour presenting this to senior recruiters acting as clients. There are several breaks during this stage. The first hour is a general presentation by Capgemini about life working there, and there is also a half an hour Q&A with current employees at the end. Generally the first stage went fairly well as it is preferable to random technical questions or a large homework assignment in the days proceeding the interview. However the second stage was a mess for a number of reasons. Firstly my business case had virtually nothing to do with Data Science, which was the role I was applying for, and put my in a fairly disadvantageous position in providing any insight. Secondly the business case presented is very barebones and expects you to assume a number of things before you can even begin to make any progress, which in real life you would simply deal with by liaising with the client. Thirdly, you're supposed to elect roles for each member within the project (technology consultant, project manager etc), yet the criteria for success completely abandons these and treat every group member as if they are supposed to provide equal insights. After several days I got my rejection letter along with feedback. This feedback was completely contradictory, claiming that I was both over-managing when addressing the technology aspects of the project (which is the job I was actually applying for and every other member was from a non-technical background) and too quiet on the strategy aspects (a role I wasn't applying for and have no experience with). My technical input was rated very well, however I didn't show "senior consultant" skills in regards to taking charge of the presentation. This seems ridiculous considering we're sorted into roles, none of which assume a senior role, and this project had nothing to do with the role I was applying for or reflective of the experience I already had as I wasn't applying for a senior position. After sending a message back asking why I was judged on senior criteria when I wasn't applying for a senior position, I was ghosted. The entire interview process seems laboriously long considering it entirely hinges on a presentation about a field you may or may not have any experience with, and relies on a presentation with a team you've never worked with. After following up nobody on my team received an offer either, which implies the process has a large amount of luck involved.

      Questions d'entretien [1]

      Question 1

      1-2-1: - How would you deal with data imbalances given more time - What is the confusion matrix telling us and how can we use that to process our data more effectively - Given the current model assessment metrics, how would you proceed Team Assessment: None of presenters asked any technical questions, they were entirely geared towards general strategy.
      Répondre à cette question
      1

      Candidature

      J'ai postulé via un établissement d'enseignement supérieur ou universitaire. J'ai passé un entretien chez Capgemini en mars 2022

      Entretien

      Un premier entretien de 20 minutes, pendant duquel je me suis présenté et j'ai parlé de mon parcours. On m'a posé des question sur mon intérêt pour le conseil ainsi que sur les raisons de mon choix de capgimini. La deuxième phase consiste à une étude de cas avec un consultant

      Questions d'entretien [1]

      Question 1

      Pourquoi Capgimini Invent? Pourqoui le conseil?
      Répondre à cette question

      Entretien pour Consultant Data Scientist

      8 févr. 2021
      Employé (anonyme)
      Hyderâbâd
      Offre acceptée
      Expérience positive
      Entretien difficile

      Candidature

      J'ai postulé via un recruteur. Le processus a pris 3 semaines. J'ai passé un entretien chez Capgemini (Hyderâbâd) en janv. 2021

      Entretien

      I got a call from company recruiter one day and she asked me the basic details and my availability for coming Saturday. Friday I got one more call to confirm my availability and they scheduled the interview. There were 2 rounds of technical interviews on the same day and HR round a week later.

      Questions d'entretien [1]

      Question 1

      Round 1: ML: Regression, classification, Deep learning, Ensemble methods, under sampling and oversampling techniques, data processing steps, complete project pipeline, evaluation metrics, underfitting, overfitting, bias-variance, entropy, gini index..., Python: same basic questions, functions of lists, pandas, numpy libraries, deep and shallow copy, finding an nth root of a number without predefined functions. Round 2: more on your project experience, challenges and approach in your projects, tools and automated tools used in the project, AWS services used, complete project pipeline using AWS, probability questions, few questions on DL, approach to a problem statement, based on your approach you will get a few more questions like why not the other way etc.., Most questions are from the things mentioned in your resume and the answers for previous questions.
      Répondre à cette question