Java, SQL, “backward chaining” … tech world lingo can sometimes sound like a foreign language. But with IT and cybersecurity talent currently in high demand, IT staffing pros need to be able to communicate with potential candidates and assess if they’re a good fit for open requisitions. That means learning their industry-specific languages.
Below are four “languages” IT staffers need to know to effectively screen for open roles in the age of tech.
Don’t worry. We’re not about to tell you that you need to speak “cybersecurity” fluently. However, you do need to be able to properly screen which candidate is best for which role. And that takes a little know-how in cybersecurity basics.
The first thing to understand about cybersecurity professionals is that they’re not just tech security guards. They’re trained to look for potential threats as well as fix those threats, stopping hackers before they even have a chance to get started. That’s why, in order to have a successful career, cybersecurity experts must understand programming languages.
According to Hackernoon, these are the five programming languages cybersecurity pros should know:
- C and C++
Learn enough about each that you can develop screening questions to find high-quality candidates best-suited for the job.
The software development industry is always evolving, which is both good news and bad. The good? It means there’s pretty much a guaranteed demand for developer jobs that IT staffing firms need to help fill. The bad? It makes it even more challenging for you to stay updated on “developer” language.
We can already hear you breathing a sigh of relief; yes, programming languages overlap for various jobs in the tech industry. After all, if developers built a software component with Legos, cybersecurity experts couldn’t analyze and solve problems using Lincoln Logs.
3. Data scientist
IT staffing pros don’t always understand the realm of data science. Many confuse it with data mining, data engineering, business intelligence, or statistics. And while it does combine different fields of work in statistics and computation, a data scientist’s primary function is to understand and interpret complex data for decision-making purposes.
Their “language” is a little more varied in that they don’t just need to know how to code; they also need statistical and mathematical skills. Not to mention proficiency in data visualization, Hadoop, SQL, and machine learning.
Though maybe one of the most important qualifications often overlooked in the data scientist screening process: How well can they tell a story? Your client probably doesn’t have an office full of data geeks. So the data scientist needs to be able to translate their findings into something everyone else can understand and care about.
4. AI/Machine learning
Artificial intelligence is no longer just a motif in science fiction dystopias — it’s here, and it’s transforming the world. Businesses aren’t exempt from this shift in technology, which is why recruiting AI/machine learning experts is critical to the future of a company.
To understand this industry’s “language,” it’s essential to recognize the distinction between AI and machine learning. AI is the software that can mimic human learning and then complete tasks faster than we ever could. Machine learning is the process by which AI learns.
Automation increases productivity and functionality throughout organizations. That’s one of the reasons AI/machine learning pros have become such a hot commodity in IT. And because this industry tends to focus on resolving problems, your candidates must have skills such as “backward chaining” (the strategy of working backward to discover the reason or cause of an issue). Getting to know some of the most frequently used terms in AI will help you better understand job descriptions, decipher resumes, and recommend top-notch talent to your IT staffing clients.