I have a Computer Engineering degree and have almost finished my Masters in Statistics/AI (both in Brazil).
And I'm having a terrible time to find a entry-level job as a Data Scientist. At this point I've done a bunch of interviews, here are some thoughts about then:<p>- Almost all places have some first phase as a internet test with hard/very specific questions about Software Engineering/Statistics/ML, all with an
infuriating time limit (one of them wanted me to code a Merge Sort in 4 minutes, fine I guess, if I had practiced this yesterday...). Oh, and 2 of these tests would disqualify you for copying or pasting text on the screen.<p>- I've been eliminated from more than one company by recruiters (after having gone through technical phases) for not having business experience (the wrong "profile"), when they specifically asked for someone with a Masters degree.<p>It seems to me that the hype on AI has broken this hiring process, there might be so many people applying for these companies that they are forced to apply these obnoxious technical interviews, as they suppose no one is qualified for the job.<p>Other problem is what they expect of a entry-level Data Scientist. It looks like it they want someone very knowledgeable about coding and statistics and business, but not having experience in the very field I want a <i>entry-level</i> job is a no-no.<p>So what do I do? One thing that got me a couple of interviews was doing a end-to-end ML project and posting about it on Medium... Should I do more of that?<p>Or go back to study the type of stuff that they want to test on these technical interviews?<p>Or try to get a job as a Software Engineer on something related to AI and then think about changing positions?
People mean everything and nothing when they say they want a Data Scientist. So you inevitably will have many interviews that don't work out because you are not what they had in mind. Same goes for those questions. They don't have a clue so they don't know what to ask.<p>Make sure you know what you want. And of course what you can and can't do. And tell them right away. Cut your losses before a long interview process.<p>Find ways to talk about yourself instead of simply answering questions. Smaller companies have less rigid interview processes(but also less knowledge about what they want) where you can talk about your knowledge and interests.<p>On the other hand, if you want to get a job with a longer hiring process, you do need to prepare for those.<p>Get to know people from the field. Go to meetups ect. That gives you the chance to present yourself, too.<p>Evaluate what you are missing that could help you get the job you want. Decide which field, data ect you are interested in. Consider what skills you are lacking if you would do a complete project in that field. You are applying for an expensive positions, so people are wary about hiring you. They want you to sound like you got this.<p>I hope you find the right job soon!
First off, what kind of companies are you applying to? The reason I ask is because the smaller the company, the more hats you'll likely have to wear as a data scientist so even though smaller companies/startups are recruiting for a data scientist, what they really mean is the entire data science department including data engineering and SME/project management capabilities.<p>If you're interviewing with larger companies, they generally tend to have more resources to hire those other skillsets so your focus as a data scientist is to create models.