•1 min read•from Data Science
Almost 15 years since the article “The Sexiest Job of the 21st Century". How come we still don’t have a standardized interview process?
Our take
Almost 15 years after the influential article "The Sexiest Job of the 21st Century," the data science interview process remains frustratingly inconsistent. While the field has matured, candidates face a daunting array of expectations—ranging from SQL proficiency to data structures and algorithms, case studies, and on-the-spot model building. This lack of standardization can make job transitions overwhelming. Meanwhile, machine learning engineering appears to have developed clearer pathways.
Data science isn’t really “new” anymore, but somehow the hardest part is still getting through interviews, not actually doing the job.
Maybe it’s the market, maybe it’s the field, but if you’re trying to switch jobs right now it feels like you have to prep for literally everything. One company only cares about SQL, another hits you with DSA, another gives you a take-home case study, and another expects you to build a model in a 30-minute interview. So how do you prepare? I guess… everything?
Meanwhile MLE has kind of split off and seems way more standardized. Why does “data science” still feel so vague? Do you think we’ll eventually see the title fade out into something more clearly defined and standardized? Or is this just how it’s going to be?
Curious what others think.
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