Hear us out. The Harvard Business Review dubbed it the “sexiest job of the 21st century” – the data scientist, alluring for a number of reasons: It’s a hot commodity position that calls for candidates highly specialized in a medley of areas including math, data engineering, analytics, and computer science. As this position is fairly new to the tech scene, recruiters sometimes struggle to land on a definition that embodies the full scope of a data scientists duties.
In its simplest form, data scientists develop analytical models using data sets to solve problems, answer questions, and to help companies make better decisions for now and the future. Not sure if your company should be hiring for this role? Here are three arguments for doing so.
Get ready to take on the data.
Think of data as your IP, intellectual property. Having more data means you’ll have more insight into people’s behaviors, and it’s not enough to understand how your customers behave, but to know what to do with that information to improve your product, decrease churn rates, and predict trends and product changes. If you don’t know how to react to customers’ behaviors, how can you help them?
To keep up with the competition, companies need to understand how to make efficient use of big data.
As more companies gain access to resources allowing them to make more data-driven decisions, having a competitive edge means orgs need to have people with relevant, up-to-date skills, and who are willing to learn how to use new technologies and tools. Being proficient at understanding and reporting on big data sets also allows teams to foresee upcoming trends in their space and to understand how to systematically grow their company.
Because by 2018, the U.S. may face a shortage of about 1.5 million managers and analysts who know how to apply big data to company decision-making.
While it may be a little early to determine if your company should be sourcing data scientist candidates now, predictions by the McKinsey Global Institute on the talent shortage can help recruiters prepare for the upcoming hiring challenges. Rather than looking at data scientists to hire for the future, consider hiring candidates with relevant skills who are interested in developing their talents to fit the role at a later date. Think of any scientists whose work is highly quantitative, requires writing code or analyzing data, or has a background studying or working in astronomy, astrophysics, physical chemistry, computational biology, neuroscience, math, statistics, engineering, or quantitative social sciences. These scientists in the industry can train and learn the tools used in analyzing big data.
We’ve got a whole webinar dedicated to teaching recruiters and hiring managers how to source data scientists on the world’s largest network of data scientists. Best thing is it's today! We’ll even teach you how Entelo can help you source and reach out to these candidates. Want in? Request the on-demand recording here!
