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 »
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 »
If you have experience in the tech staffing business, you may have noticed a recent rise in the amount of fraud and dishonesty in the marketplace. This is perhaps inevitable given the high level of demand for data engineering and data science skills. So, how can you separate those candidates who can walk the walk
Resume fraud: Warning signs and how to protect yourself 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 »
Data science is, and has been, in vogue. Every forward-thinking company wants to have a data science program because by now it is conventionally understood that it will improve profitability and efficiency across the business. To some companies with troves of data waiting to be ‘data scienced,’ this means hiring data scientists willy-nilly even if
Step 1: Collect data. Step 3: Profit. Step 2: Hire data scientist? Read More »
Many companies focus on hiring permanent employees for their data science roles when, in some cases, data science contractors might provide a convenient, more readily available solution while also offering other advantages. If you’re like many of the analytics leaders and HR professionals we talk to, you know how hard it is to build a
Need a data scientist? Why you should consider data science contractors. 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 »
What is Hashing? Hashing is simply passing some data through a formula that produces a result, called a hash. That hash is usually a string of characters and the hashes generated by a formula are always the same length, regardless of how much data you feed into it. For example, the MD5 formula always produces
What does it mean to hash data and do I really care? Read More »
Predictive analytics is this super-complex field that only statisticians and data scientists can understand, right? Well, perhaps it takes some training to do it well but it only takes two sentences to understand what it’s all about: In predictive analytics we determine the likelihood of something by looking at data about it. We do this
Data Science and Predictive Analytics Explained in Two Sentences Read More »
