For those who think there’s a lot of fraud in resumes today… you\’re right! We\’ve seen thousands of resumes over the years and, undoubtedly, we’ve seen a lot of fraudulent ones. With resume fraud being so rampant, separating out fraudulent submissions is a critical piece of what we offer our staffing and recruiting customers. Spotting […]
Resume Fraud: Would This Company Use This Software? Read More »
As we discussed in what may be our most viewed Dataspace blog post (ever!), insurance is one of the oldest data science based businesses – using math to make predictions about the future. In today\’s post, we’ll be highlighting some ways in which data science has infiltrated, influenced, and innovated the insurance industry! There are
Be Assured, Data Science Ensures Success for Insurance Read More »
As you move your infrastructure to the cloud, it’s important to consider how to not become beholden to a single cloud vendor. In other words, to attain cloud neutrality. I’m afraid that I don’t have all the answers on how to do this, but I do have some thoughts. In any case, I recommend that
Why you need cloud neutrality Read More »
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 »
The last edition of our newsletter focused on some very creative applications of data science tools and methods. Most of these were lighthearted, merely reflecting the interest of the creators in their subject matter – like true scientists, they applied their skills to the questions that interested them. In contrast, today’s newsletter delves into some
Technology, progress and ethics: a balancing act Read More »
Being that data science is a relatively new field, we often get questions regarding compensation for various data science-related skillsets across different locations and industries. The healthcare and medical industry, specifically, has been a major employer of data scientists, and that demand is only growing. But similar to all other industries, healthcare data scientist salaries
Heathcare Data Scientist Salary – How Much Should I Pay? 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 »
Dataspace CEO, Ben Taub, was featured in a Dice post offering some clever suggestions for hiring data scientists and ensuring your data talent is excellent. We encourage you to take a peek and absorb some of the wisdom within! Read 8 Tips for Hiring Great Data Scientists on Dice.com
Dataspace featured in article about hiring data scientists Read More »
We begin many blog posts by highlighting the acute shortage of data scientists and the resultant difficulty in attracting them to your company. Chances are that if you are reading this, you are well aware of that fact and may have already found ways to make your organization more appealing to the data science candidates
Change this one thing about your company to help you hire better data scientists Read More »
Tools and techniques for management reporting and analysis have evolved since computers first came out. One can argue that the first management reporting tool was COBOL (COmmon Business Oriented Language). It allowed business people to get data out of systems created by computer people. COBOL was eventually replaced for reporting by tools like Information Builders
What’s The Difference Between Business Intelligence and Data Science? Read More »
