Data Scientists Are Quitting Their Jobs?!




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See all articles here:
https://www.analyticsvidhya.com/blog/2019/12/5-key-reasons-data-scientists-quit-jobs/#:~:text=How%20do%20you%20collect%20and,data%20scientists%20quitting%20their%20jobs.
https://towardsdatascience.com/why-so-many-data-scientists-are-leaving-their-jobs-a1f0329d7ea4
https://www.ft.com/content/49e81ebe-cbc3-11e7-8536-d321d0d897a3
https://www.rdisorder.eu/2017/09/13/most-difficult-thing-data-science-politics/
https://www.knowledgehut.com/blog/data-science/data-scientists-are-leaving-their-jobs
https://www.techrepublic.com/article/why-its-your-fault-your-data-scientists-keep-quitting/
https://conductscience.com/are-data-scientists-leaving-jobs/
https://techjobs.sulekha.com/techpulse/why-data-scientists-leaving-their-job-is-becoming-increasingly-common_19392

Data scientists leaving their jobs appears to be coming from the following key reasons:
1) Overall macro-economic expansion experienced between 2011-2020
2) Expectations not matching reality
3) Data scientists don’t like playing politics
4) Being the “go-to” person for all things data related
5) Lack of upskilling opportunities

Source


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Comment List

  • RichardOnData
    November 14, 2020

    Hey Richard, thx for the video. I really enjoyed it. I am concentrating on web scraping right now,since I believe for a beginner it is the fastest way to start making money/ get some real on the job experiences with data science. Does it make sense to you? Would you say that there is a better way than web scraping to start with as a freelance data scientist? P.S.: I am learning SQL and Python for nearly a year, so my question is not a about skills data scientists need the most but about where to start getting some real on the job experiences.

  • RichardOnData
    November 14, 2020

    I m ok with bit of politics I am 18 year and I love mathematics and and want to enter into this field .I am enrolled in Btech CSc (from average college)on campus program and online Bsc degree in data science (from IITM ranked best engineering in India)
    Should You encourage me to continue

  • RichardOnData
    November 14, 2020

    Instructors who provide clean data sets beyond the first example or assignment or project are doing a disservice to their students. I enjoy cleaning data, acquiring primary and secondary data, and getting to really understand the data.

  • RichardOnData
    November 14, 2020

    Hey Richard, thanks for all ur videos, I learnt a lot from your videos. Have you got any experience with Forecasting?

  • RichardOnData
    November 14, 2020

    Didnt notice you have so few subscribers. Subscribed! Great content! Constructive criticism : You could improve your narration voice – it's kind of monotone ✌️🙂

  • RichardOnData
    November 14, 2020

    Thank you sir, I find your videos helpful. Appreciate your efforts.

  • RichardOnData
    November 14, 2020

    6- expectations about auto machine learning

  • RichardOnData
    November 14, 2020

    The resemblance to Ian Hecox is uncanny here….

  • RichardOnData
    November 14, 2020

    Just adding some facts about politics in DS: especially in traditional industries, usually DS won't help with decision making at all, because the reality is: "the boss has already had a decision, and then he asks DS to conduct analysis to glorify his decision as a data-driven highly intelligent and scientific decision." Then the problem would be: when the DS's analysis results contradict the boss's decision, then the boss would get mad, disputing the DS as incapable, saying that the DS's analysis is all garbage, asking the DS to redo the analysis again and again… until the DS adds tricks or even falsifications to make the results conform to the boss's thought.
    The above scenario happens in academia as well. Many advisors care more about if the results conform to their experience, rather than scientifically right or wrong.

  • RichardOnData
    November 14, 2020

    Richard, I would love to see a video on the top things in your opinion that a company needs to have in place culturally and infrastructure-wise to support data scientists and a data department. Keep up the good work.

  • RichardOnData
    November 14, 2020

    First 🤩

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