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      Entretiens chez FanDuelEntretiens d’embauche pour Product Analyst chez FanDuelEntretien chez FanDuel


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      Entretien pour Product Analyst

      27 juil. 2022
      Candidat à l'entretien anonyme
      Aucune offre
      Expérience neutre

      Autres retours d’entretien d’embauche pour un poste comme Product Analyst chez FanDuel

      Entretien pour Product Analyst

      7 déc. 2020
      Candidat à l'entretien anonyme
      New York, NY
      Aucune offre
      Entretien moyen

      Candidature

      Le processus a pris 2 mois. J'ai passé un entretien chez FanDuel

      Entretien

      Slow process with HR. 1 call and then an initial interview. After the initial interview, I had a SQL test and presentation to make. In my next/final interview, I presented my presentation and went over a couple of the SQL problems. Fine interview.

      Questions d'entretien [1]

      Question 1

      How much money did a starbucks in times square make last monday in an hour (1-2pm)?
      Répondre à cette question
      Expérience négative
      Entretien facile

      Candidature

      J'ai postulé en ligne. J'ai passé un entretien chez FanDuel (New York, NY) en nov. 2020

      Entretien

      Same as all the other negative reviews regarding this role. It was easily one of the most unprofessional interview processes I've ever had, and I've had many interviews for this type of role. No screening with a recruiter. Sent me a dataset with questions such as: using this data, what specific recommendations do you have for improving the product? Felt like a ploy for free consulting advice. That said, finished the project in a few hours, submitted and no response. Sent a followup in a week with again no response. Would never again interview for and will deter anyone I know from choosing to use or interview with FanDuel.

      Questions d'entretien [1]

      Question 1

      Using this data, what specific recommendations do you have for improving the product?
      Répondre à cette question
      3

      Entretien pour Product Analyst

      16 févr. 2020
      Candidat à l'entretien anonyme
      New York, NY
      Aucune offre
      Expérience négative
      Entretien moyen

      Candidature

      J'ai postulé en ligne. Le processus a pris 2 semaines. J'ai passé un entretien chez FanDuel (New York, NY) en janv. 2020

      Entretien

      Fanduel was by the worst interview process that I've been through. The main reason why I'm rating it as a negative is because of the poor communication from HR regarding the status of the interview, especially after they give an assignment, which the recruiter mentioned usually takes a week to complete. I applied for this role online, didn't even have a screening call with the recruiter. I was asked to complete a case study that had 3 parts. Part 1: Excel assignment Very simple, you were given an excel spreadsheet. They provided data on 11 sports stars, whey they have buy items against the clock. You have to perform tasks like Clean the name format of the players, compute the final price of the players given a discount, find the top spender in each category, create a control box chart. There were 11 total questions Part 2: SQL Given a schema of a database that consists of a user table, entry table, game table, and payments table. They asked the following questions: The CRM Manager has an idea for a test and wants to know how many users have made at least one deposit, registered in 2018, and played at least one NFL contest in 2018. What is the SQL code needed to answer this? You and the CRM Manager agree that the number of users is sufficient for this test. Now it’s time to generate the list of users to be sent the email. With the same constraints as above, you need to generate a list with the following fields, so that the CRM Manager can start to build custom segments: user_id email total entry fees for NFL in 2018 total entry fees for the other sports combined in 2018 the number of winning entries the user has ever had the percentage of entries on mobile across ALL sports in 2018 the last paid entry date of the user the total net deposit value, i.e. deposits – withdrawals The Marketing VP is concerned there has been a movement away from head-to-head (2 player) games over the last 3 years for NFL. S/he believes it may be a reason for declining retention and wants you to investigate. Specifically, s/he wants to know in each year between 2016 and 2018 what percentage of entries and entry fees were head-to-head games in each user’s first 30 days after registration. What is the SQL code needed to answer this? Part 3: Product Assessment FanDuel offers many DFS contests across many sports. The Contest Lobby is the place in our product where customers can find the DFS contests they want to enter. Contests in the Lobby are constantly being updated as contests fill (i.e. the maximum number of seats in the contest has been reached) and new contests become available. The order in which contests appear in the Lobby can change depending on which segments a customer belongs to (e.g. beginner, intermediate, advanced, a certain geography, etc.). If you haven’t already done so, feel free to create a FanDuel account and explore the Contest Lobby to get a feel for it. What key metrics would you look into to monitor the health of the Contest Lobby and why are these metrics important? Provide a list of specific ideas (at least 3) you have for improving the Contest Lobby along with any key metrics you feel would be relevant for measuring the success of these ideas, and your reasoning for why these metrics are relevant. In the second part of the product assessment, I was given a The attached fictitious dataset (titled: DATA for Product Assessment 2019) includes: FanDuel User ID Platform(s) used in the last 12 months (“native” = FanDuel iOS or Android app, “web” = desktop or mobile website) NFL entry fees in the last 12 months MLB entry fees in the last 12 months NBA entry fees in the last 12 months I had to answer the following questions: What does the data tell us about our business and our customers? Based on any findings or insights you’ve gleaned from the data, what specific recommendations do you have that could help the business grow, inform the prioritization of product and/or marketing efforts, etc.? For each of your recommendations, can you model out the value of what you’re proposing? Be sure to include notes about any assumptions you’ve made. The tasks weren't difficult; it was very time-consuming. After doing all this week, at least communicate the status after the interview.

      Questions d'entretien [1]

      Question 1

      What does the data tell us about our business and our customers?
      Répondre à cette question
      3