How To Land A Cybersecurity Job Even If You’re Not A Data Scientist
The cybersecurity skills gap is large, well-documented, and quite possibly yawning wider by the week. Not only has the information security industry grown an estimated 62% since 2011, but we’ve seen an increasing deluge of major data breaches over that same period. In past year alone, devastating hacks at Equifax, Uber, and the NSA have brought to light how much work still needs to be done to keep the world’s data secure. And the cybersecurity company Symantec predicts that 2018 will see a rise in cybercriminals conducting ever more sophisticated attacks, including with the help of artificial intelligence.
The upside for job seekers, though, is a growing wealth of opportunities in an expanding field. In fact, here at The Data Incubator, which offers data-science training and job placement (including through a free fellowship program), we’ve seen demand for data experts in security-related fields double over the past six months.
For those who are data scientists already, the key to landing one of those jobs is to expand your knowledge base beyond data science itself. You need to relate to the human element–the source both of the data you’ll be working with and of the threat you’ll be defending against. For those with backgrounds outside data science, the job-search challenges differ. Here’s what it takes to land a cybersecurity job, no matter what your skills and experience might be.
Getting Into Cybersecurity As A Data Scientist
Industry experience isn’t always required. When companies hire for their data security teams, they typically expect data-science applicants will be coming from different fields. Protenus, a health compliance analytics firm in Baltimore, boasts a team of PhD data scientists with experience ranging from particle physics to quantitative marketing. That diversity of experience helps the company’s data security team take novel approaches to challenges, build smarter systems to analyze huge data sets, and solve multifaceted problems quickly.
So if you’ve worked as a data scientist in other roles and applications, your experience is probably more transferrable than you think. The key is being able to articulate–step by step–how you tackled previous data challenges. Showcase your problem-solving skills; hiring managers will want to know you can see all sides of a data problem from the perspective of every stakeholder.
Expand beyond technical skills. Whatever you do, don’t neglect your communication and project-management chops. Data scientists don’t work in a vacuum, especially not in the highly integrated organizational functions that cybersecurity requires. You’ll need to collaborate with engineers and security experts, and maybe even external customers and other industry partners. The ability to communicate the technical aspects of your work in jargon-free terms, and to stay organized all the while, are critical qualifications for data scientists working in security roles.
Not A Data Scientist? Don’t Worry
Start developing your data analysis and programming skills. You can do this while you’re actively applying to data security positions–then mention it in your application and on job interviews. If you’re excited about the field but aren’t yet a data scientist, that may not count against you; employers have many other roles to fill that aren’t as technical, with the expectation that new hires will learn on the job.
In the meantime, you can take a class on data analytics or programming, or even just an introductory overview (we offer one here). You can also start getting familiar with R or Python programming, and develop your own project to showcase your problem-solving skills. The key is to show employers your ambition and ability to learn.
Just get your foot in the door. One advantage to working in a fast-growing field like cybersecurity is the ability to advance quickly. So be okay with not doing your exact dream job right away–you can always work your way into it. Experience with policies and procedures is crucial in data security–for instance, how to handle personal and private data–not just the computing skills. So as you build up that hands-on expertise, you’ll be able to move ahead, even if you never become the most talented technical wizard on your team.
Get straight on the underlying values. Companies aren’t just looking for candidates with skills and experience but also those who grasp the core values around data privacy and security. Highlight why–on a personal level–you can have an impact, and how your values align with the organization’s. Understanding whether candidates share the company’s goals and objectives around data security can help put you over the edge in a competitive hiring process.
Experts predict that the growing skills gap will lead to a global shortage of some 2 million cybersecurity professionals by 2019, while the field’s unemployment rate will remain at 0%. All the while, the threats will grow at a similar pace, locked in an arms race with no foreseeable end. Meeting the enormity of that challenge will require many more people–data scientists and otherwise–to jump into the fray.
Michael Li is the founder and CEO of The Data Incubator. A data scientist, Michael has worked at Google, Foursquare, and Andreessen Horowitz. He is a regular contributor to VentureBeat, The Next Web, and Harvard Business Review.
Nick Culbertson is cofounder and CEO of Protenus. Prior to Protenus and his time at medical school, Nick served eight years in the U.S. Army as a highly decorated Special Forces operator (Green Beret). He was awarded two bronze stars during his service, one for extraordinary valor. Nick is also a Tillman Scholar and has spoken on the topics of AI in healthcare in forums across the country.