Transition to Data Science is rough..

Acxiom gunghojoe
May 3, 2018 14 Comments

On the market for new D.S. job after 2 yrs experience. Got some interviews but can't get past tech screens. My background is experimental psych, but I programmed in Matlab a ton during my phd and postdoc. Picked up R and Python, but I'm not very good at either. Picked up sql in the last job (stint as data analyst at startup) so now I'm mediocre at 4 languages and bombing out of these interviews.. squandered Netflix, Uber, Abnb already. Got more lined up. Hackerrank all day, kaggle til bed...

I've never worked so hard to fail so hard. I'm keeping at it until interview opps fizzle, but any ideas for new career direction for me? Anyone want to help me grow into an effective data scientist? Could use some mentorship for sure.

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TOP 14 Comments
  • Microsoft / Eng
    yKId44

    Microsoft Eng

    PRE
    Amazon
    yKId44more
    Failure rate is high in this stint. Practice, Practice, and Practice. Throw dice as many times as possible!
    May 3, 2018 3
    • Microsoft / Eng
      yKId44

      Microsoft Eng

      PRE
      Amazon
      yKId44more
      Failure rate is high even for people already in the field. Don't beat yourself up over it.
      May 3, 2018
    • Monsanto gunghi🧝🏻
      Here is the catch - how do you practice for DS, in other words what topics do you focus on? DS is too broad, unlike SWE, where you do 600 leetcode questions, prepare for design rounds and if you crack it, you have a job!
      May 3, 2018
    • Acxiom gunghojoe
      OP
      I'm applying for predictive modeling/ml, Analytics, and inference ds roles which compliment my background training, but am training up on classification and cluster ml analysis. So I'm tackling interviews focused within that spectrum of data science.

      May 3, 2018
  • Axtria nyc!
    I have been in data science for a while now, and yes, it is hard, very hard. Mainly because it's not focused on one thing, unlike swe interviews where you can just leetcode and get through. Even if you code a lot, or solve lot of kaggle case studies, or whatever, you still flunk because the interviewer can ask you literally anything in the world, like probability or statistics or algorithms or business case studies.

    Just keep giving interviews and you will get better at it. One tip I can give you is to prepare your resume well. You should be able to speak for 10mins on every single line in your resume, and you should exactly know the ml algorithms that went behind each of your resume projects.

    I mentor a lot of data scientists so feel free to ping me.
    May 5, 2018 0
  • Airbnb SNHM28
    you'll be fine. just make sure to get feedback, work on answering product and business questions, and polish your takehomes.

    eventually you'll find the niche where you have an edge. data scientists don't have to be amazing coders by any stretch.
    May 3, 2018 0
  • Cisco Tacjdd
    Data science is just hard. I’ve worked as a data scientist for four years at two different jobs and only now do I feel like I’m getting better at interviews. Finding job number 2 with two years of experience felt just as hard as finding job number 1. I too felt as if I had only learned bits of things with no solid experience in any one thing.

    Don’t worry, keep trying. Experience will accumulate. You may need to try lower tier companies this round.
    May 3, 2018 0
  • I have a few years of experience and still crash and burn at interviews, sometimes at tech portion or sometimes at the end, during the face to face. What I have noticed however, is that every time it becomes easier. So just take it as practice, you'll eventually hit it :)
    May 4, 2018 0
  • LinkedIn tVfy86
    Which aspects of the interview are you struggling with? Coding? Stats/ML? Case questions?
    May 3, 2018 2
    • Acxiom gunghojoe
      OP
      Coding for sure. Not a huge problem with stats. I'm simply green at ML. Getting more mature daily, but not there yet.
      May 3, 2018
    • LinkedIn tVfy86
      Try datacamp. Good examples in either R or python that are specific to DS.

      Sounds like you just need practice to get fast. Stick to it and it’ll click. I came from a consulting background and was in your position many years ago, now I’m a sr DS.
      May 4, 2018
  • Acxiom gunghojoe
    OP
    I appreciate the encouragement and tips
    May 4, 2018 1
    • Uber STarly
      Apply for DS jobs in marketing, they may appreciate your background more.
      May 20, 2018
  • Zapier pRdl83
    My two-cents from a similar background. Look at the specific subteams you'll be working with. Where is the data coming from? Humans? You've a leg up. Do they want black box models or to understand their data. Do they care about peering into the black box? You're a particular type of scientist, play to and look for jobs that match your strengths. You don't need to start out with a big SV name. The small companies are starving for real talent; take a risk.
    May 20, 2018 0