Appearing For A Data Science Interview? Be Prepared For These 7 Types Of Questions. Here we are listing seven types of questions that data science candidates should be prepared for.
Appearing for data science interviews can be a dreadful task for many candidates due to the fear of the unknown in the interview process. To acquaint data science enthusiasts, especially freshers, we even cover a weekly feature on data science hiring processes in different companies. It aims to give them an insight into the skill sets required, the growth opportunity, along with the educational background that is required and most importantly, the kind of questions asked. Based on our past interactions with the companies we are listing seven types of questions that data science candidates should be prepared for.
Usually designed for freshers entering the field, puzzles are the warm-up interview questions that tend to analyse a candidate’s approach towards solving a problem. Moreover, it tests the logical and analytical aptitude of the candidate, which are the key criteria for a job in the analytics and data science domain. Many tech companies such as Google and Microsoft include puzzles and riddles as a part of their interview process. Below are some puzzles that data science freshers can prepare for their upcoming interviews.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
They say, the first impression is the last, and thus resumes are the first impression of any professionals including data scientists while searching for a job.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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If you have other resources, tips, or advice, please leave a comment below and I’ll update this post for others looking to advance their data career.