You've spent months studying data science, now it's time to find a job in the industry. Fortunately, companies all over the world are looking to hire data scientists -- and fast. According to LinkedIn's 2020 U.S. Emerging Jobs Report, skills related to Machine Learning, Deep Learning, TensorFlow, Python, Natural Language Processing, etc. seen more than 70% annual growth. According to an IBM survey, the openings for data and analytics talent in the US will continue to increase, reaching 133% growth in 2020, and creating more than 700,000 openings. Qualified candidates will have a multitude of vacancies to choose from when ready to seek out a new position in the field.
Preparing for an interview is not easy – naturally there is a large amount of uncertainty regarding the data science interview questions you will be asked. No matter how much work experience or technical skill you have, an interviewer can throw you off with a set of questions that you didn't expect. For a data science interview, an interviewer will ask questions spanning a wide range of topics, requiring strong technical knowledge and communication skills from the part of the interviewee. Your statistics, programming, and data modeling skills will be put to the test through a variety of questions and question styles – intentionally designed to keep you on your feet and force you to demonstrate how you operate under pressure. Preparation is a major key to success when in pursuit of a career in data science.
Are you aspiring to become a data scientist, but struggling to crack the interviews? Getting a break in the data science field can be difficult. Doubly so, if you're coming from a non-data science background (which in all likelihood you are). The stories you hear from other aspiring data scientists can make interviews feel more intimidating and daunting. So you better be prepared before facing the interviews. What kind of questions can be asked? How can you prepare and what are the resources you should refer to? What is the structure of a typical data science interview? How should your body language be? These are just some of the questions you'll have in mind.
Becoming a data scientist is considered a prestigious trait. Back in 2012, Harvard Business Review called'data scientist' the sexiest job of the 21st century, and the growing trend of roles in the industry seems to be confirming that statement. To confirm this sexiness is still ongoing, the info from Glassdoor shows being a data scientist is the second-best job in America in 2021. To get such a prestigious job, you have to go through rigorous job interviews. Data science questions asked can be very broad and complex. This is expected, considering the role of a data scientist usually incorporates so many areas.
Hiring a data scientist can be a tricky process. The actual definition of "Data Scientist" is vague, the day-to-day job of someone with "Data Scientist" in their job title varies dramatically between organizations, and people come to the field from a wide variety of backgrounds. Examining the past of a data scientist candidate is a science in itself, one worthy of a blog post of its own. Today we're going to stick to building an interview that examines the present. Most data scientist job interviews fall short of exploring the full range of topics necessary to determine a proper fit.