As someone who has been looking for Data Scientist jobs in the past few months, I can reliably say that the term can mean everything from software engineer for

As someone who has been looking for Data Scientist jobs in the past few months, I can reliably say that the term can mean everything from software engineer for big data systems, SQL guy or a person that builds complex machine learning models. It is just as vague as the job profile of a "programmer". In that sense, the title is right. But, in the context of the article's content, I disagree. The job done by a data scientist in demanding roles, requires a strong grasp on undergrad level statistics. But because of the recent trends towards ML, the person also needs to have a strong grasp of linear algebra, vectorization and software engineering / undergrad algorithms. While it is unlikely that one data scientist may need to summon the whole skill set, an interviewee will never know which subset of these skills you will be asked to demonstrate to get hired. Modern software jobs have figured out distinct subset of skills needed to differentiate between different software roles for experienced employees. Junior level employees are barely even expected to know anything other than algorithms, data structures and high level system design (at least during interviews) Another funny observation (anecdotal) is there seem to be more openings for "senior data scientist" (who is expected to know everything), than "junior data scientists" whom the company is willing to mentor. As of now, I find myself scrambling to decide which skills I need to prioritize, often feeling like I am being pulled in opposite directions. Almost of which require formal instruction (the maths), and can't be picked like software skills through youtube and online projects. This isn't a knock against software, just different type of subject matter. Companies interviewing for these roles may ask everything from leetcode algorithms questions to statistics to questions about modern ML algorithms and domain specific models (in NLP, Vision, finance, recommenders) I personally find a "junior" Data Scientist's role (in expectations) to be harder than that of a junior SDE. There is a reason many these jobs will put phD into preferred qualifications. It is ironic that there has been such a massive surge of people without the necessary background, who do a couple of MOOCs and crown themselves data scientists. Being good at any software & math heavy domain is hard. Data Science is no exception.