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      Entretiens chez ManulifeEntretiens d’embauche pour Senior Data Scientist GENAI chez ManulifeEntretien chez Manulife


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      Entretien pour Senior Data Scientist GENAI

      26 mai 2026
      Candidat à l'entretien anonyme
      Toronto, ON
      Aucune offre
      Expérience négative
      Entretien facile

      Candidature

      J'ai postulé en ligne. J'ai passé un entretien chez Manulife (Toronto, ON) en mai 2026

      Entretien

      The interview process is a bit of a joke to be honest. After initial recruiter conversation I was told that next round will be a case presentation which will be sent to me 48 hours in advance. Initially I thought the case might be something simple where it will take 2-3 hours of my time. When it arrived I was blown away by the requirements. They wanted me to develop end to end production level solution for one of the use cases which is just too relevant for their day to day. The requirements included working code whcih should generate live logs during the call. The requirements included in the requirements document itself mentioned that the case should take 8-10 hrs. Seriously are they expecting candidates to dedicate 10 hrs of their time (trust me it will take more if you are doing it diligently) - almost full 2 days worth of work just before the interview? The interviewer himself (the newly promoted director of data science) was rude and seemed disinterested during the call. I dont know whats wrong with the company but the least they could have done is be polite and actually look like you want to be there when a candidate has poured so much blood sweat and tears creating the whole project for you in 2 days. Honestly it reflects more about their culture than anything else. I wish luck to anybody who got through the process since I dont want to work for the company who is so unprofessional and just want the candidates to work for free for more than 12 hrs.

      Questions d'entretien [1]

      Question 1

      Designing a rag pipeline for case
      Répondre à cette question

      Autres retours d’entretien d’embauche pour un poste comme Senior Data Scientist GENAI chez Manulife

      Entretien pour Senior Data Scientist GENAI

      15 mars 2026
      Candidat à l'entretien anonyme
      Toronto, ON
      Aucune offre
      Expérience négative
      Entretien facile

      Candidature

      J'ai postulé en ligne. J'ai passé un entretien chez Manulife (Toronto, ON) en janv. 2026

      Entretien

      They will send you a take-home assignment 2 days before the interview, with no prior notification, and expect you to have it completed by the interview. Complete disregard for your time and plans. After the interview, they will ghost you.

      Questions d'entretien [1]

      Question 1

      Basic questions about implementation and overall RAG.
      Répondre à cette question

      Entretien pour Senior Data Scientist GENAI

      6 avr. 2025
      Candidat à l'entretien anonyme
      Aucune offre
      Expérience positive
      Entretien moyen

      Candidature

      J'ai postulé en ligne. Le processus a pris 4 semaines. J'ai passé un entretien chez Manulife en mars 2025

      Entretien

      Screening (30 min, virtual): With HR rep. Asked about experience, why I'm looking for a new role, salary expectations. Asked me to walk through one of my Gen AI projects. Asked me what I would if a Gen AI solution broke down. Left 10 min at the end for questions. Technical Round 1 (60 min, virtual): With DS team. 15 min LeetCode Easy (using an IDE of your choice with AI assist turned off), 30 min Gen AI experience based on resume, 10 min foundational stats and machine learning questions, 5 min for questions. Technical Round 2 (60 min, in person): With VP and Senior DS. Comprised of technical and behaviour-based questions.

      Questions d'entretien [3]

      Question 1

      LeetCode "704. Binary Search". Given an array of integers nums which is sorted in ascending order, and an integer target, write a function to search target in nums. If target exists, then return its index. Otherwise, return -1. You must write an algorithm with O(log n) runtime complexity.
      1 réponse

      Question 2

      RAG: - What model did you use? - How would you process different kinds of structured data? - How would you work with images and text? - What vector database did you use? - How many GPUs? - What is the architecture of an LLM? Explain different types of transformers and their use cases. When would you want to fine-tune an LLM? What ingredients are needed to get a good result?
      Répondre à cette question

      Question 3

      What is bias/variance tradeoff? What are some regularization techniques? Explain each one. What are some techniques to assess goodness of fit?
      Répondre à cette question

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