Opinion: How to secure the best tech talent
The pandemic has created a frenzied expansion of DevOps roles fuelled by cloud-based activity, and the automation of different tech stacks to deploy and write code. Faced with managing the advent of so much more cloud-based development, companies are frantically looking for DevOps professionals with the experience required to maintain continuous and even accelerated development.
There are other tech roles also in high demand. It’s no secret that a great data scientist is hard to come by, but an all-in-one data wizard who possesses every skill required to conceptualize, create, maintain and productionalize successful data models that can drive business decisions – is a rare breed indeed.
Those worth their salt are frequently snapped up by multinationals, leaving a small subsection who may prefer to work for a tech start up or scale up – however, they may need convincing.
What can tech companies actually do to secure the best talent in an age where hiring just got harder?
Tap into a Trade Secret
Here’s a trade secret: when it comes to complex roles that are in high demand, you would think it would be very difficult to attract the right candidates. Yet in fact, the opposite is actually true. It’s actually remarkably easy to target these people because they are digital natives, and likely to be present on digital marketing channels.
Because tech people have specific skills that are related to specific technologies, it makes sense to use these as keywords in digital marketing campaigns. For instance, if you’re recruiting for DevOps roles and you throw out buzzwords Amazon AWS, Azure, RedShift, and digital products like Jenkins – if you target recruitment activities against these words, you’re going to hit DevOps people. Similarly, if you target keywords like Hadoop and Python, you’re going to hit data scientists.
If firms can embrace digital attraction, and use it as an element in a dedicated recruitment marketing strategy, it may go a long way to ensuring that the correct people see the job adverts and campaigns - and to make sure recruitment budget is not wasted on unqualified candidates.
Social media can also be a big help in targeting people who meet specific criteria. While traditional job board adverts can be seen by anyone who uses appropriate search terms, targeted social media ads can only be seen by people who meet specific criteria. This could be qualifications, experience, specific skill sets or even location; with Facebook, LinkedIn and Google targeting capabilities, there are a range of possibilities which can ensure only suitable candidates see your ads.
Stop Chasing Unicorns
The data science polymath is about to become as rare as another Newton or Goethe. Instead of trying to hire multiple unicorns, organizations may be better off following a more flexible approach to getting the data science talent they need.
It’s better to use your own best people to define the data sub-specialisms and hire against that. The data scientist is a new and evolving position, and the same criteria will not likely fit for everyone. With data science roles, you have to have an evolving view of what a senior, intermediate or junior position looks like and requires.
Someone may have done a master’s degree in data science, but the fact is, these courses for the most part have only been around for a few years. By the checkbox criteria, that person may not yet have the skills to be a data scientist in a lot of organizations. It’s a new discipline which will fragment over time, and specialty qualifications will emerge within it. Organizations must understand the complexities of the roles and be more flexible in their hiring practices in order to secure good data science talent.
Recruiting for highly specialized roles is a bit of a new discipline, and companies need to begin to look at non-standard routes to hiring. Limiting roles so severely and only considering, for example, Ivy League or Oxbridge maths graduates with several years’ worth of experience is unlikely to end up in success. There may be candidates with 10 years of experience or industry veterans who are perfect, but who did not attend the very top elite schools.
Beyond this, online education is improving at a Moore’s Law type of pace. Components of data science can be learned to a practical level without the need for a STEM PhD. Hiring for raw aptitude or transferable skills can pipeline talent for scale.
Consider the Passive Candidate Market
LinkedIn is a useful recruitment platform, and their paid job ads are pretty good, but there's a key flaw. The key flaw with LinkedIn is that it only addresses the active candidate market. If there are five million software developers in the US, only 15 to 20% of them may be actively looking for positions.
Relying wholly on platforms like LinkedIn means you've ignored 80% of potential candidates. With the right message and the right communication, tech companies may be able to attract someone who wasn’t even looking for a new role in the first place. It’s a bit like advertising: the same way companies win new customers for products people didn’t even know they needed or wanted, companies may be able to attract new candidates.
When it comes to hiring and scaling, tech companies certainly have their work cut out for them these days, but with a little innovation, and an open minded and flexible approach, firms can be well positioned to attract the very best tech talent, and to continue scaling products competitively.