(Towards Data Science) Red flags in data science interviews
We liked this opinion by Jacqueline Nolis* for the value it offers to candidates, hiring managers, and HR alike. To be clear, the piece is written for candidates – the author’s intended audience is specific to those interviewing for Data Scientist jobs – and she provides great tips for assessing a company’s data science infrastructure, processes, and priorities.
But if hiring managers pay close attention to the author’s suggestions, they’ll find great tips for improving their candidates’ experience and leaving a strong impression. At a minimum, think of the article as a list of ‘what not to do’ (and check-out our tips for creating an excellent candidate experience). Among other suggestions, Jacqueline tells candidates to watch out for an unstructured interview process, inconsistencies in interviewers’ description of the role, and the lack of a clear plan after onboarding.
Are you making any of these mistakes? We find that they’re common (…too common) and applicable beyond Data Scientist interviews. Top candidates display higher levels of excitement and confidence in a business which they believe is well-organized, and they make that judgment through the lens of the interview process. Read the article to see your interview process through their eyes. And if you need help organizing your talent acquisition process or making a strategic hire, get in touch. We are here to listen and help.
*Jacqueline is a Principal Data Scientist and independent author writing in Towards Data Science, on Medium‘s publishing platform.