AI News, Here’s why so many data scientists are leaving their jobs

Here’s why so many data scientists are leaving their jobs

Many junior data scientists I know (this includes myself) wanted to get into data science because it was all about solving complex problems with cool new machine learning algorithms that make huge impact on a business.

The data scientist likely came in to write smart machine learning algorithms to drive insight but can’t do this because their first job is to sort out the data infrastructure and/or create analytic reports.

In reality, if the company’s core business is not machine learning (my previous employer is a media publishing company), it’s likely that the data science that you do is only going to provide small incremental gains.

The first few sentences from that article pretty much sum up what I want to say: If you seriously think that knowing lots of machine learning algorithms will make you the most valuable data scientist then go back to my first point above: expectation does not match reality.

That may mean that you have to constantly do ad hoc work such as getting numbers from a database to give to the right people at the right time, doing simple projects just so that the right people have the right perception of you.

It reeks of a job spec from a company that has no idea what their data strategy is and they’ll hire anyone because they think that hiring any data person will fix all of their data problems).

Now if a data scientist spends their time only learning how to write and execute machine learning algorithms, then they can only be a small (albeit necessary) part of a team that leads to the success of a project that produces a valuable product.

On the other hand, if the goal is to optimize provide intelligent suggestions in a bespoke website building product then this will involve many different skills which shouldn’t be expected for the vast majority of data scientists (only the true data science unicorn can solve this one).

So if the project is taken on by an isolated data science team it is most likely to fail (or take a very long time because organizing isolated teams to work on collaborative project in large enterprises is not easy).

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