Why so many data scientists are leaving their jobs

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Yes, I am a data scientist. And yes, you did read the title correctly. Someone just had to say it.

We read so many stories about data science being the sexiest job of the 21st century and the attractive sums of money that you can make out of it. The field also contains an abundance of highly skilled people geeking out to solve complex problems. It seems like the absolute dream job!

But the truth is that data scientists typically “spend one or two hours a week looking for a new job,” says this article. It goes on, saying that while machine learning specialists topped their list of developers who said they were looking for new jobs, data scientists were a “close second.” These data were collected by Stack Overflow in their survey based on 64,000 developers.

I, too, have been in that position and have recently switched jobs.

So, why are so many data scientists looking for new jobs?

Before I answer that question, I should clarify that I am still a data scientist. On the whole, I love the job and I don’t want to discourage others from aspiring to be data scientists because it can be fun, stimulating, and rewarding. The aim of this article is to play devil’s advocate and expose some of the negative aspects of the job.

From my perspective, here are four big reasons why I think many data scientists are dissatisfied with their jobs.

1. Expectation does not match reality

Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.

This quote by Dan Ariely is so apt. Many junior data scientists I know (myself included) wanted to get into data science because it was all about solving complex problems with cool new machine learning algorithms that make a huge impact on a business. This was a chance to feel like the work we were doing was more important than anything we’ve done before. However, this is often not the case.

In my opinion, the fact that expectation does not match reality is the ultimate reason why many data scientists leave.

Every company is different so I can’t speak for them all, but many companies hire data scientists without a suitable infrastructure in place to start getting value out of AI. This contributes to the cold start problem in AI. Couple this with the fact that these companies fail to hire senior/experienced data practitioners before hiring juniors and you now have a recipe for a disillusioned and unhappy relationship for both parties.

2. Politics reigns supreme

3. You’re the go-to person for everything data

4. Working in an isolated team