While we may yet be a long way from the threat of truly sentient computers such as Hal 9000 and ARIIA, the current capability of AI technologies still offers plenty of power for those who wish to harness it for malicious purposes. These types of crimes go beyond the grey ethical areas that we discussed […]
Danger, Will Robinson! (AI, Analytics and the Invisible Dangers) Read More »
A note to technical recruiters: There’s a difference between a data scientist and a Python programmer who knows some data science frameworks We’ve recently heard from a number of technical recruiters who’ve been burned. They were tasked with finding technical talent who could cover the standard data science bases: Python (or R), Pandas, scikit-learn, and
A Big Mistake Technical Recruiters Make Read More »
As many a frustrated recruiter or hiring manager can tell you: a good data scientist is hard to find, and even harder to hire. Quality candidates frequently end up with multiple final round interviews (often within days of each other) leading to multiple offers. In such a competitive environment, your challenge is to figure out
Making your company more appealing to data scientists Read More »
The process of screening candidates for any role can be both daunting and time consuming, and even more so when the role in question is a highly technical position such as a Data Scientist. The ever growing list of tools and technologies that these professionals work with can read like a foreign language to recruiters
What to look for in a data science resume Read More »
Trends seen throughout the majority of 2017 persist in the current job market—low unemployment rates and rapid job growth across multiple sectors. These factors have combined to create a highly competitive hiring environment and a shortage of highly skilled professionals—especially in fields that have seen a higher than average job growth rate such as data
Should we be more open to sponsoring analytics talent? Read More »
