Author: Stephanie Glen<\/p>\n
If you plug “statistics interview questions” into a search engine, you’re going to get hundreds of questions and answers. And if your interview is looming in a few days, trudging through (and trying to memorize) hundreds of questions probably isn’t your idea of a fun weekend. And if you’re looking for that shoe in, having the perfect answer to every question might not be your best plan of attack. Why? Because that’s what everyone else is doing.<\/strong><\/p>\n So how do you stand out from the crowd? It won’t be by knowing an answer to an obscure question (e.g. what is lambda calculus?<\/em>). You’ll stand out by being a memorable candidate. <\/strong><\/p>\n When you interview for a data science position (or any other position), you’ve already been placed into a homogeneous group.<\/strong> You can bet that all of your fellow interviewees have a data science degree (or whatever degree was specified), and x<\/em> years of experience. What’s important to remember here is that your interviewers are real people, and (despite having their objective score sheet), they are simply looking for a team player that’s going to fit in. When the interviewing team goes to review the top candidates, you want to make sure that you’ve left a big impression–one they aren’t going to forget.<\/p>\n So what can make you stand out? Mine your background for something that’s interesting<\/strong>, and find an opportunity to drop it into the interview. You’re almost always going to be asked about your biggest achievement, your proudest moment, a time when you almost gave up, or something similar.<\/p>\n My go to: mushing<\/strong>. I trained for a year leading up to one race (the Aviemore rally)<\/a>, mostly teaching my dogs how to run in a straight line, turn on command, and ignore rabbits (if you’ve ever owned a husky, you’ll know what that last part is the hardest!). What I should<\/em> have done was trained for a marathon. On the day of the event, I ran next<\/em> to my dogs going uphill, so that the sled was lighter and they could run faster. Half way around the course, my lungs were on fire and my legs were jelly. But I had trained for so long, I wasn’t about to give up. When we finally crossed (staggered over) the finished line, I collapsed into a heap, utterly exhausted. I won first place, but that’s not really the point. My takeaway? Put in 100%, even when it seems like you’re not going to make it.<\/p>\n So why is this important?<\/strong> I told this story at my interview for Ford Motor Company in the early 90s. Other than my mushing skills, I had no degree at all, and best of all: I completely flunked Ford’s computer science aptitude test.<\/em> I left school at 16 with zero qualifications (unless an O level in art counts) and it showed. But my interesting background impressed the manager so much, not only did I end up getting the job, Ford ended up sponsoring my mushing activities the following year!<\/p>\n So before microfocusing on those data science interview questions, make sure you’ve mined your background for a unique story that will make you stand out. A memorable nugget or two<\/strong> will end up being much more valuable than your memorized answers to standard interview questions.<\/p>\n<\/p>\n<\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"