BubblyBiscuit
BubblyBiscuit

The reality of fancy data science roles

Everyone thinks data science is such a hot role and you get to work on cool stuff, but the reality is NOT glamorous! 80% of the job is cleaning messy data, fancy algorithms are useless without business context, networking is as important as coding skills, if not more. Who you know matters.

6mo ago
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GroovyWaffle
GroovyWaffle

When do you draw the fine line between 1)when a data scientist should clean the data himself and 2) a data scientist saying that this data is shit and cannot be worked on at all ?

PrancingCupcake
PrancingCupcake

Depends on value vs time tradeoff. You write it off when, effort is too much and the results will be shit

BouncyNugget
BouncyNugget

Yeah a lot of machine learning jobs don't even do actual machine learning.

A friend I knew long ago was doing a data science job even after mba.

SqueakyQuokka
SqueakyQuokka

The problem is that most Data scientists don't even clean data. They just pick and train a model on it.

SqueakyWaffle
SqueakyWaffle

I’d love for all of you to join our interactive community, where professionals can share ideas, ask questions, and collaborate on topics like DSA, AI, and Cloud. It’s the ideal space to connect, learn, and grow together!

https://chat.whatsapp.com/CwjB8veGy6EBGdZkBbVUur

Can’t wait to see you there!

JumpyQuokka
JumpyQuokka
Student6mo

well then it's then you who is engineering data if there is not data engineer at your org

DizzyJellybean
DizzyJellybean

It depends on the company you join and the exposure you get. For instance in my company as a data scientist I am responsible for end to end life cycle of a project - starting from data gathering all the way till production including scheduling of the models.

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