"Data scientist" has already been declared this year's hottest job, and now a new report offers several more reasons to consider it as a career. For the past three years executive recruiter Burtch Works has been surveying data-science professionals about salaries and other related topics. Burtch Works defines data scientists as professionals who can work with enormous sets of unstructured data and use analytics to get meaning out of them. Published on Thursday, this year's report is based on interviews with 374 working data scientists, and it paints a pretty compelling picture. Here are five particularly attractive highlights.

We are a group of experts, PhDs and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM. We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science. Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.

What kinds of technology-related courses did students pursue this year? Based on new data from Coursera, it's clear that data science, Python, and artificial intelligence (A.I.) are on the minds of the next generation of technologists. Coursera, a massive online learning platform, has provided a breakdown of its most popular courses in 2019. "AI and related tech-centric content attracted interest like never before," read the blog posting accompanying Coursera's data. "2019 is the year AI became accessible to the masses, rather than just for engineers."

O'Reilly has released the results of the 2016 Data Science Salary Survey. This survey is based on data from over 900 respondents to a 64-question survey about data-related tasks, tools, and the salary they receive from doing/using them. The median salary reported in the survey was US 87,000; amongst data scientists in the US, the median salary was US 106,000. Appropriately for a survey about data science, O'Reilly doesn't merely report aggregate statistics from the survey; they fit a linear regression model for a data, and extact coefficients from the model indicative of salary "bumps" (or downgrades) attributable to demographic factors. Factors that tended to increase salary included: working in cloud computing environments; working with Python; and being older.

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