Unexpected skills you must hone to get hired
My company Evo is expanding, which means we’ve been through a few hiring cycles in recent months, something that will continue throughout 2021. We are looking for data scientists that can hit the ground running and quickly integrate into the team.
And yet, we continuously struggle to find the right people. It’s not that the technical skills aren’t out there. We see hundreds of applications with years of advanced math, statistical modelling experience, coding skills, and comfort with Python libraries like Pandas and Numpy. Unfortunately, many applicants fail to highlight the non-technical skills critical to success as a data scientist.
Yes, you obviously need technical skills to carry out tasks, but you can learn technical skills quickly on the job. If you have a basic understanding of how to code, you can apply those skills to new languages and switch to other environments and libraries without too much trouble. It takes a lot longer to teach someone the soft skills vital for optimally deploying those technical skills.
The Covid-19 crisis made Big Data even more important. Data scientists will be in greater demand in 2021 — but only those data scientists equipped with the unique skills needed to meet this moment. There are four critical skills every employer will expect data scientists to have in 2021: skills every applicant needs to demonstrate from the start.
1. Communication skills
The client always comes first, so we are in constant, open communication with our clients. Every data scientist needs to be able to respond effectively to client requests, questions, and concerns, both in delivered solutions and in simple communications.
It’s not enough to simply have a model that solves a business problem. You also need to be able to explain how the model works and why it is making a particular suggestion. Just 11% of companies using AI are getting significant ROI. Why? They don’t understand how it works and, in turn, don’t trust recommendations or use the AI properly. This leads to opportunity costs that are untenable in a post-Covid world. AI must be accessible to deliver on its promises. For that, data scientists must be excellent communicators.
Of course, not all roles have direct contact with clients. Even for candidates who will likely never speak to a single client, however, clear communication is a priority. Like many companies, Evo transitioned to a fully remote workplace this year, and we have had team members around the world since we were founded. Collaborating remotely is impossible without strong communication skills.
To complete critical tasks, whether you are developing a new function from scratch or debugging code, you need to be able to quickly and concisely explain your work to others on the project. Poor communication skills = wasted time and confusion. Poor communication causes the average corporation $62.4 million in lost productivity every year. No company can afford that right now.
2. Project management knowledge
Another 2020 trend caused by an increased move to remote work: increased employee independence.
Team members must manage their own work, personally responsible for deliverables without the structure of the office.
In the recruitment process, we need to determine that new hires won’t find this independence and personal responsibility overwhelming. Demonstrable project management expertise is a simple way to gauge this. Even if only on a smaller level, such as managing a personal coding project as a hobby or leading a project team for a university course.
The need for project management skills will only increase in importance in 2021 onwards. In this post-Covid world, data scientists must be more agile to deal with changing conditions. Every team member must be able to juggle critical tasks and adjust without losing track of the ultimate goals. These are the same skills you develop when running your own projects. Even in an entry-level position, some project management experience makes you a much better candidate.
3. Automation mindset
A top technology trend in 2021 will be automation. Businesses have recognized that AI-driven automation is the best way to compete in the Digital Age. Banks and insurance companies predict an 86% increase in AI-based automation by 2025, and hyperautomation has been listed as a key strategic trend by Gartner again for 2021.
How does this apply to potential data scientists? If the average employee needs to value AI automation to succeed, data scientists must embrace it even further. It’s not enough to simply know how to create autonomous models; you must make it a priority any time you are designing an algorithm. Automation must drive you and be an integral part of everything you build. Business science must be autonomous, not just data-driven, to be effective, and every data scientist must actually be a business scientist.
An automation-first mindset sets candidates apart.
Plus, an automation mindset saves time! When you automate your own simple and repetitive tasks, it frees you up to focus on more complex and valuable — not to mention more interesting! — projects. No company is going to hire a data scientist who resists automation when automation is the future.
4. Business acumen
As I mentioned above, every data scientist must be a business scientist to get hired. What’s the difference?
A data scientist is driven by the data: Here’s some data; what can we do with it? A business scientist is driven by business objectives: Here’s a business problem; what does the data suggest we can do to solve it?
There’s a reason I promote business science over data science: data is only helpful if you leverage it to solve the right business problem. Unless you know what challenges your clients and your industry face, you will never come close to achieving optimization.
When we are evaluating a candidate, we don’t care if you can create the most elegant algorithm in the world unless that use of the data serves a business objective. Knowing the difference requires business acumen. As a data scientist, you must understand the problems your business wants to solve to effectively leverage the data and deliver an accurate and actionable analysis. You cannot get hired in 2021 without demonstrable business knowledge and comfort in the areas where your clients operate.
The secret to getting hired in 2021
The secret to getting hired in 2021 isn’t a secret after all; it’s soft skills that match the high calibre of your technical skills. Highlight your successes in these four areas right alongside your technical accomplishments on your resume to secure a job.
If you are looking for a job as a data scientist right now, your prospects are good. The need for data scientists is growing rapidly, and skilled data scientists are in high demand. But that won’t matter unless you can show that you aren’t just a technically proficient data scientist. You must be a true business scientist who has honed these four skills.
About the author
Fabrizio Fantini is the brain behind Evo. His 2009 PhD in Applied Mathematics, proving how simple algorithms can outperform even the most expensive commercial airline pricing software, is the basis for the core scientific research behind our solutions. He holds an MBA from Harvard Business School and has previously worked for 10 years at McKinsey & Company.
He is thrilled to help clients create value and loves creating powerful but simple to use solutions. His ideal software has no user manual but enables users to stand on the shoulders of giants.