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If you are an aspiring data scientist preparing for a career in the field of machine learning, you might have considered penning down a strategy to crack a machine learning job interview.
Chance favours the prepared mind
This year, the India Skills Report 2018 revealed that about 47% of future jobs in India will be in the areas of Analytics, Artificial Intelligence, and Robotics. Another global survey by GMAC Corporate Recruiters Survey Report 2018 estimated a 52% hike in hiring projections in the field of data analytics. These stats are encouraging enough for every data scientist in India to thoroughly prepare for the upcoming job opportunities.
If you are one of them, you can significantly increase your chances by improvising your interview approach and learning a few hacks which will help you a long way in your machine learning interview.
Three incredible hacks to crack ML job interviews
1. Applying probability to interview too
A majority of roles for analytics professionals in India focus on text analytics and natural language processing. This is followed by image analytics and lastly audio and speech analytics. So emphasize their proficiency in the same order to showcase your job readiness and skill relevance to the interview panel.
Sound theoretical knowledge is fundamental to every data analytics role. A clear understanding of various machine learning models like Bayesian Method, Linear Regression method, neural networks and how they are applied for problem-solving can help you breeze through the most recurring ML interview questions.
Pro tip – Linear regression being the most applied statistical technique in data science, you must know it like the back of your hand. While at it, improve your grasp over logical regression too.
2. Approach vs Knowledge
Having a methodology and a scientific approach is important for a scientist. Same applies for analytics and interviewers are keen on screening candidates on the same by asking machine learning interview questions that test your approach. Here are some commonly asked machine learning interview questions you should prepare for.
* What is the difference between supervised and unsupervised machine learning?
* How is Bayes Theorem applicable in machine learning?
* Explain how a ROC (Receiver Operator Characteristic) curve works?
*How would you handle imbalanced data sets if you were to encounter them?
If you have prior experience in document exploration system, you should document it in your resume as it will surely draw the interview’s attention.
It should be noted that while explaining it to the interview panel you dwell on your approach and why it worked in this particular case. For example, how you classified data, how you extracted it from different sources like images and documents, why clustering with LDA technique worked in this scenario etc.
Pro tip – While you may want to prove your technical grasp over the subject, in most cases the interviewers are evaluating you on your approach and how coherent your thought process is.
Source - thisisbespoke
Full dress rehearsal
This may sound like a no-brainer but reading up sample questions and going through mock interviews online can help you prepare for the most obvious. Typically, a machine learning interview revolves around programming fundamentals, probability and statistics as well as data modeling and evaluation. You can prepare a list of questions on each of these subjects and do a full dress rehearsal to practice answering them without any hitches or breaks.
Pro tip – Read up case studies on the website of the interviewing company and connect them to your answers related.
A machine learning interview prep is the first and the foremost step towards starting a career in machine learning. Having a strategy for it will help you multiple times in your career and that’s where these hacks will always come in handy.