One of the biggest challenges companies face today is the big data talent gap. Businesses want to use big data, but in order to do that, they need to have the right personnel on hand capable of performing those tasks. This is a tall order for many organizations, mostly because good data scientists are hard to come by. The demand for talented data scientists is high, but sadly the supply is low. Universities and other educational institutions are working hard to teach a new generation of data scientists, but were still years away from even coming close to having supply reach demand. That means businesses have tough decisions to make when it comes to hiring a data scientist. While they certainly want to make the best hire possible, its just as easy to get that decision wrong. With this in mind, here are several things to keep in mind to make sure you dont make the mistake of hiring a bad data scientist.
Perfection Doesnt Exist
A data scientist that has mastered every single programming language, has become an expert in each big data platform, and is the top of the class at statistics, mathematics, and development is often called a unicorn. And just like in the real world, unicorns dont exist. It may be tempting to hire to instantly hire a data scientist who claims their proficiency in all these different areas, but chances are they are selling you something they cant possibly deliver. Perhaps they do have experience in multiple platforms, programming languages, and other areas of big data influence, but its next to impossible to master all of them. Look at data scientists promising the world with a great deal of skepticism.
Real World Experience
Its easy to practice big data in a controlled environment. Its another thing entirely when data scientists are thrust into the real world. Many data scientists may boast about their experience with big data in an academic setting, but theres no substitute for actually getting out there and working with real world data for a business. That means data scientist should demonstrate their skills by applying their talents to solve actual business problems, not developing a theory about how those skills could be used. Of course, every data scientist needs to get started somewhere, but when hiring for a top data scientist position at your organization, you need to look for someone with real world experience.
The Importance of Teamwork
Data science is best done in teams. There may be some data scientists that want to take all the credit and all the glory for the results, but just like with any sports team, that approach will only serve to erode team chemistry. A data scientist that cant work as a team player is one that will cause problems. Data science teams work best when members of the team are open about sharing data and insights with each other. They work as one in order to reach their own goals and those the company has set for them. This also means a data scientist with poor communication skills is one that will fail to achieve the right results more often than not.
Mathematical Knowledge
Data scientists can come from all sorts of backgrounds, but one of the best ones to look for in a background in mathematics. Performing big data analytics may include use of programming skills and computers, but its in mathematics where data scientists truly prove their worth. A great computer developer may be able to achieve a lot with computers, but if they have a poor understanding of mathematical principles, they wont get very far with big data. On the other hand, an excellent mathematician with poor programming skills can usually learn programming to the point where theyre able to use it effectively. The key comes down to the ability to interpret data, and mathematical knowledge is one of the top skills to have for that area.
Hiring a bad data scientist can be a real setback for any organization. Since big data is such a new field, its easy to get that hire wrong. Knowing about the warning signs and understanding what specifically to look for can help you make the best decision. When you do hire a capable and skilled data scientist, youll quickly see the benefits he or she can provide your company.
