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      Jobs at Comcast

      5 jobs in United States
      Data Scientist 2 - Virtual
      Philadelphia, PA
      ·
      $75K - $157K /yr
      (Employer provided)
      View job
      Sr. Data Scientist - Virtual
      Philadelphia, PA
      ·
      $105K - $209K /yr
      (Employer provided)
      View job
      Machine Learning Engineer (GoLang)
      United States
      ·
      $143K - $214K /yr
      (Employer provided)
      View job
      Lead Software Engineer (AI) - Onsite - Reston, VA - Freewheel
      Woodbridge, VA
      ·
      $46K - $82K /yr
      (Glassdoor est.)
      View job
      Sr. Measurement Science Lead
      New York, NY
      ·
      $130K - $196K /yr
      (Employer provided)
      View job

      Comcast interviews FAQs

      • Candidates applying for Director of Data Science roles take an average of 60 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at Comcast overall takes an average of 27 days.
      • Common stages of the interview process at Comcast as a Director of Data Science according to 1 Glassdoor interviews include:

        Presentation:  25%

        Group panel interview:  25%

        Phone interview:  25%

        One on one interview:  25%

      • Here are the most commonly searched roles for interview reports -

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    • Director of Data Science Interview

      Nov 3, 2017
      Anonymous Interview Candidate
      Radnor, PA
      No offer
      Negative experience
      Difficult interview

      Application

      I applied online. The process took 2 months. I interviewed at Comcast (Radnor, PA)

      Interview

      I applied through LinkedIn and got a call from an internal recruiter, who was very pleasant and enthusiastic. I passed the initial phone screen and was invited to do an in-depth phone interview with a peer. I spent about an hour on the phone at this stage, answering technical questions and learning about the role. I was subsequently invited to the next stage. I was asked to do a data science project using a dataset they would supply. In retrospect, I should have refused. I spent several hours building a predictive model and putting a PowerPoint deck together, which I presented to the same person who interviewed me. It started to become clear at this point that the person interviewing me didn’t know as much about the technical content as I did; I felt like I was providing free consulting. I was then invited to an on-site interview. The interview lasted about half a day and included around 10 people. One person on the schedule never showed. In general, I found the interviewers arrogant and not very sophisticated. One person had me go through some old-school thought experiments. In the first, he asked me why there are more escalators going up than down in a typical train station. I answered that one correctly, so he then asked me to estimate the number of light bulbs in Philadelphia. He didn’t like my answer on this one and made me guess about how he preferred to answer the question. With other interviewers I got a lot of questions on the predictive modeling process, ranging from data cleaning and feature engineering to favorite algorithms, preventing model overfit, and managing very large feature sets. My sense was that I knew more and had vastly more practical experience in these areas than anyone interviewing me. Nevertheless, I thought o did a good job of being patient and personable and engaging with the process in a constructive way. I never heard back. It has been a complete waste of time all around. Never again.

      Interview questions [1]

      Question 1

      How do you manage a predictive model that has 30,000 features?
      Answer question
      3
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