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21 Reason why you should NOT become a Data Scientist


Time for some Friday Fun!

In last few years, the growth of Data Scientists has been following the growth in data . You can see it all around – people attending webinars, info sessions, undergoing multiple certifications and what not!

While everyone is going North, I thought Friday is a good time to take a moment and head South!


Source: Pinterest


Here is my list of 21 reasons why not to become a Data Scientist. If you have a few others to add, please do so!

1. Trump: When every data scientist in the world got it wrong!


Source: Uproaxx

If no one could predict such a macro phenomena, how would they know who is going to buy what?


2. At times you’ll get it horribly wrong. Did I just say ‘wrong’? Epic FAILURES! 


Remember the Twitter bot from Microsoft? She started saying great things about Hitler with 1 day of training on live data.


3. Ever participated in Kaggle? This is how I feel when you have to spend days getting that small increase in the 5th decimal place.

3-5th-place-decimal-accuracySource: megaaa.kyu.mobi

Not to mention the days when I don’t get even a slight increase in my scores irrespective of what I try.


4. And in case, I got awesome results from a black box model – this is how it feels! 

I have no clue what happened.

5. Torture the data and it’ll confess what you want it to.


Source: Pintrest

At times, you can use data to create any point you want!


6. Why study so many algorithms when XGBoost always does the trick for you!


Source: Giphy


7. Automation! My job is to make machines replace me.


Who on earth in sane mind wants that?


8. I must learn the languages that are going to pass out in 10 5 years anyway.

Or at times the ones, which many people have not even heard of!


9. Looks like I’m the only one who calculates the p-value of getting an increment everyday.



10. I get bashed by the CEO daily while everybody stands and watches.


Source: Knowyourmeme

What people don’t realise is that I’m the only person whom they take advice from!


11. Nothing is impossible until you start to explain Data Science at a social gathering.


Source: Giphy


12. Human thinking ends at 3-D. My work starts at 100-D.

13-slicing-and-dicingSource: Giphy


13. Carrying cool laptops is a dream. Carrying servers is a necessity.


Source: ASUS


14.   Only god knows the future. Whom am I to predict.



15.  Astrologers have been doing it for years.


Source: Imgflip


16. Why spoil weekends over a hackathon/competition? Coldplay?



17. I am expected to teach domain expertise to domain experts.


Source: France Etiquette Limited


18. Any my expertise depends on where I’m giving the interview.


Source: Pinterest


 19. Don’t doubt me. Alternative hypothesis stands true!


Source: Pinterest



20. No one knows who a Data Scientist is?


But everyone is searching for one!


21. The world is a strange place. And believe me, it’s not at all like what you think.


Disclaimer: This is just a fun take on life as a Data Scientist. We don’t intend to hurt any sentiments or endorse any products / services mentioned above. We truly believe, data science is here to stay, else we would not have bet our careers on it 🙂



End Notes

I hope you enjoyed reading this article as much as I did while writing it. If you are a data scientist, you will definitely relate to some of the points above. Which one did you relate to the most? Also, any point you think we missed in this list?

Share them with us in the comments below.

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  • Vinay says:

    At times this is me…
    4. And in case, I got awesome results from a black box model – this is how it feels!

  • Nitesh says:

    Haha good one!

  • Dev says:

    Ha ha hilarious!!!

  • Sambid Kumar Pradhan says:

    haha 4th one

  • Nishant says:

    Loved 8th, 9th & 14th.

  • Asesh Datta says:

    I found your presentation motivating right from pt. no. 1 to 21. Data Scientist is a jargon which we always encouraged as ‘Talk with data’. You need a scientist to handle volumes of data and interpret what we want to share.
    That is the problem. Our duality kind of interpretation is the most detrimental. Right or wrong, good or bad, improving or deteriorating, black or white, left or right, happy or fear and many more. And there is mid point to all these diplomatically, neutral.
    Data scientists can paint a picture and create a vision. Then there will be an opposition and another vision will be portrayed.
    Value of a data scientist will be measured once both views are considered (including neutral stance) and provide a non-dual perspective (not necessarily third view). This is tough unless believed and attempted. Thanks for the article.

  • Janpreet Singh says:

    Ha ha! you got it right in the Apple 😀

  • Ananthasireesh says:

    seriously are you scaring me

    – A Data Scientist aspirant

    • Saurav Kaushik says:

      Hi Ananthasireesh.

      It’s just a fun post. These are some things that you might go through during your journey as a Data Scientist. I believe even you might be able to relate to some of them. I feel there is absolutely no reason to be scared.

  • Jim Roberth says:

    Nice Article, proper for friday.

    I’m not sure, but since a couple years ago many people who take only a course online are named by themselves as “specialist” or senior analysis in linkedin, no matter the years of experience nor the studies they are specialist or seniors.,

    I’m not so sure where is going to go this because if you put a specialist with 1 year of experience as CEO advisor is he going to crash the company?.

    Anyway maybe I’m talking because I’m a little bit upset about that, but if in the meanwhile there isn’t a institute (such as PMI) who is recognigzed across the world who certifies who is a real data scientist , BI Specialist, or Analytics Analytis (whatever combination) we would have many high specialist or senior specialist with 1 or 2 years of experience.

  • Nice! Love the humor and right on points made that can only be best described through humor. Thanks.

    Twitter: @mitchData

  • Nathaniel Grinnell says:

    I love it. One more, ‘I have seen the truth….and it makes no sense!’

  • Charles Sutton says:

    Made my day. Domain expertise to domain experts one of my pain points. I’m trying to get data to answer the right business questions for my sales team, but they don’t know what questions to ask about their business. So who knows more about their business, them or me?

  • Varun Rajasekaran says:

    Nice article…doing aCAP and CAP conducted by INFORMS would definitely aid

  • Cynthia says:

    Brilliant. Thank you.

  • Eric says:

    Bravo for citing Tay as an example for when otherwise brilliant projects can go very wrong.

  • pujitha says:

    14 th seems true, when my prediction is not true

  • Rishabh Shukla says:

    quite motivating too !

  • Shivdeep says:

    LOL! Hilarious! good one.

  • tbqguy says:

    Saurav … bahut badhiya likhen hain..

  • Kriti says:

    Googling a syntax issue in Python and suddenly I am reading item-item based collaborative filtering….Data Science has no beginning or end… !