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Make Your Own Job in Data Science: A High-Risk, High-Reward Approach


This article discusses an alternative approach to finding data science jobs that’s also worth considering, although it has some inherent risks: make your own.



By Charlie Custer, Dataquest.io

This is an excerpt from the recently-released Dataquest.io Career Guide, specifically the chapter How and Where to Find Great Data Science Jobs.

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Pramp CEO Refael Zikavashvili suggested an alternative approach to finding data science jobs that’s also worth considering, although it has some inherent risks:

“If the candidate pro-actively sends me an email and tells me, ‘Look, I believe that you have this business challenge and this is how I would go about solving that,’ that will super impress me,” he says. “Somebody who can actually identify problems just based on public information and more than that will go the extra step and actually suggest a way to solve that, that will blow me away.”

“That person gets an instant basically interview from me,” he says. “No questions asked. I would even skip the resume at that point.”

This approach could be used in lieu of a traditional job application, Refael says, but he also recommended applicants try it with companies they’re passionate about even if that company doesn’t have an open data science job listing.

“Find a company that you really like, that you’re passionate about,” he suggests. “Analyze that company. Find a challenge that you think you can help with. Come up with a solution. That’s the best advice that I can give somebody. That’s a way to stand out.”

In theory, this approach (we previously wrote about it here) can work because it very quickly communicates three things that employers like to see in their job applicants:

  1. You’re passionate about their company and solving its problems.
  2. You have the business sense and technical skills needed to address those problems and propose a solution.
  3. You’re proactive and strongly self-motivated.

Needless to say, this is a highly risky strategy. It requires a lot of prep time: you’ve got to conduct extensive research on the company in question, identify a real problem, and do a little data science project to solve that problem in some way. Then you’ve got to find the right person to contact and communicate your work to them very quickly and clearly. If any part of that goes wrong, you’ll have spent a lot of time on a single job application and gotten nothing in return.

It’s an approach we would recommend considering only with companies and jobs you reallywant — the kind of company you’re 100% sure you’d join if you got a job offer from them.

You can also apply a lower-stakes version of this approach at companies where you’ve applied traditionally and been granted an interview—we’ll discuss this in more detail in the chapter on job interviews.

 
Bio: Charlie Custer is Content Marketer at Dataquest.io, and is a content creator of all types, but especially: writer, editor, and motion designer and animator specializing in 2D After Effects work.

Original. Reposted with permission.

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