Sauravkaushik8 Kaushik — Published On December 2, 2016 and Last Modified On December 2nd, 2016
Analytics Vidhya Beginner Listicle


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.


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.

You can test your skills and knowledge. Check out Live Competitions and compete with best Data Scientists from all over the world.

About the Author

Sauravkaushik8 Kaushik
Sauravkaushik8 Kaushik

Saurav is a Data Science enthusiast, currently in the final year of his graduation at MAIT, New Delhi. He loves to use machine learning and analytics to solve complex data problems.

Our Top Authors

Download Analytics Vidhya App for the Latest blog/Article

22 thoughts on "21 Reason why you should NOT become a Data Scientist"

Vinay says: December 02, 2016 at 6:45 am
At times this is me... 4. And in case, I got awesome results from a black box model – this is how it feels! Reply
Nitesh says: December 02, 2016 at 6:55 am
Haha good one! Reply
Dev says: December 02, 2016 at 7:12 am
Ha ha hilarious!!! Reply
Sambid Kumar Pradhan
Sambid Kumar Pradhan says: December 02, 2016 at 7:22 am
haha 4th one Reply
Nishant says: December 02, 2016 at 8:15 am
Loved 8th, 9th & 14th. Reply
Asesh Datta
Asesh Datta says: December 02, 2016 at 8:29 am
Saurav, 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. Reply
Janpreet Singh
Janpreet Singh says: December 02, 2016 at 9:04 am
Ha ha! you got it right in the Apple :-D Reply
Saurav Kaushik
Saurav Kaushik says: December 02, 2016 at 9:15 am
Hey Asesh. Well said. Couldn't agree more! Reply
Ananthasireesh says: December 02, 2016 at 1:27 pm
seriously are you scaring me - A Data Scientist aspirant Reply
Saurav Kaushik
Saurav Kaushik says: December 02, 2016 at 1:48 pm
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. Reply
Jim Roberth
Jim Roberth says: December 02, 2016 at 3:16 pm
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. Reply
Mitch Sanders
Mitch Sanders says: December 02, 2016 at 4:13 pm
Nice! Love the humor and right on points made that can only be best described through humor. Thanks. Mitch Twitter: @mitchData Reply
Nathaniel Grinnell
Nathaniel Grinnell says: December 02, 2016 at 4:35 pm
I love it. One more, 'I have seen the truth....and it makes no sense!' Reply
Charles Sutton
Charles Sutton says: December 02, 2016 at 6:28 pm
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? Reply
Varun Rajasekaran
Varun Rajasekaran says: December 02, 2016 at 7:27 pm
Nice article...doing aCAP and CAP conducted by INFORMS would definitely aid Reply
Cynthia says: December 02, 2016 at 8:26 pm
Brilliant. Thank you. Reply
Eric says: December 03, 2016 at 12:59 am
Bravo for citing Tay as an example for when otherwise brilliant projects can go very wrong. Reply
pujitha says: December 03, 2016 at 6:37 am
14 th seems true, when my prediction is not true Reply
Rishabh Shukla
Rishabh Shukla says: December 03, 2016 at 3:41 pm
quite motivating too ! Reply
Shivdeep says: December 04, 2016 at 12:44 pm
LOL! Hilarious! good one. Reply
tbqguy says: December 08, 2016 at 2:38 pm
Saurav ... bahut badhiya likhen hain.. Reply
Kriti says: December 09, 2016 at 10:26 am
Googling a syntax issue in Python and suddenly I am reading item-item based collaborative filtering....Data Science has no beginning or end... ! Reply

Leave a Reply Your email address will not be published. Required fields are marked *