Data Science

Let’s talk money. As a “hot” career right now, data science can pay pretty well. But for an individual person matched with a specific job or industry, how much should someone expect to make? 

Since Katie was on the job market lately, this was something she’s been researching, and it turns out that data science itself (in particular linear regressions) has some answers. 

In this episode, we go through a survey of hundreds of data scientists, who report on their job duties, industry, skills, education, location, etc. along with their salaries, and then talk about how this data was fed into a linear regression so that you (yes, you!) can use the patterns in the data to know what kind of salary any particular kind of data scientist might expect.

Careers in Data Science

O'Reilly's Mike Hendrickson chats with database pioneer and 2014 Turing Award recipient Michael Stonebraker about winning the award, the future of data science, and the importance — and difficulty — of data curation.

The Future of Data at Scale

Paco Nathan and Jesse Anderson on the evolution of the data training landscape.

O’Reilly’s Ben Lorica chats with Paco Nathan, director of O’Reilly Learning, and Jesse Anderson, technical trainer and creative engineer at Confluent, about the training landscape in the big data ecosystem, their teaching techniques and particular content they choose, and a look at some expected future trends.

Data Science

Eugene Ismailov