Data is becoming more important than ever. In a connected world, companies can now extract data from a variety of sources like marketing, sales, customer service, and operations.

 

By analysing this data, it gives them valuable insights into their business. This allows them to improve their decision-making abilities and implement new strategies to improve their business processes. Ultimately, it improves their efficiency, productivity, and revenue when they’re able to implement these changes.

 

As a result, data scientists are in high demand and will continue to be for years to come as increasing amounts of data becomes available. Simply put, increasing amounts of data mean more analysis, more insights, and the ability to further improve business processes.

 

So, you’re probably reading this because you want to hire a data scientist for your business. More importantly, though, you probably want to know what some skills are you should look out for when doing so.

 

Let’s take a look.

 

Coding

 

Make no mistake, the best data scientists should know how to write code and be comfortable with a variety of programming tasks. This is simply because data science, to a large extent, relies on gathering data, cleaning it, and implementing algorithms to gain insights from data, all through the use of code.

 

The two most popular programming languages for data science are Python and R. There are also some other languages that data scientists use, like Scala, Java, and C++. However, these are not in as high demand or as popular as Python and R.

 

It’s also important to keep in mind that, although R was very popular in data science a few years ago, Python is now the go-to language. As a result, many data science libraries and tools are coded in Python and many new data scientists entering the scene focus on improving their Python skills.

 

Another benefit with Python is that it does more than just data science. It’s also used extensively in disciplines like machine learning, deep learning, and artificial intelligence. Because these technologies are becoming so popular and more businesses are using them, it’s important that the data scientist you hire have some of these skills to implement them in your business.

 

Education

 

Education is an interesting aspect to look at. Years ago, it was a fixed requirement that any programmer or data scientist have a relevant degree to qualify for a job. So, is education important? Well, the answer is not as simple.

 

In a recent analysis of data scientist job postings, most job postings asked for a master’s degree or higher in computer science, statistics, or mathematics. It then appears that education is important. Fortunately, though, most of the job listings stated that the requirement of a master’s degree as a good to have. In other words, it was not essential.

 

Also, with the wealth of platforms and services available online, many people are learning the skills necessary to become data scientists without having to complete a degree. As a result, it’s more important that you look at whether the candidate has the necessary skills and experience to do the job and get the results you expect of them.

 

This means, irrespective of whether the candidate has a degree not, it’s crucial that the candidate has skills like data intuition, iterative design, and statistical thinking. At the end of the day, you should look for someone that can bring the most value and do the job. If they can, the question whether or not someone has a degree becomes irrelevant.

 

Background

 

To a certain extent tying into the question of education, background could also play a role in data science. In the analysis mentioned above, the data scientist job listings were about equally split between a background in statistics, computer science, and mathematics. Just like education, the question is whether a candidate’s background is essential in a data scientist role. Here, the answer is also it depends.

 

Think of it in this way, would you rather hire a candidate with a background in computer science but without the skills to do the job or would you choose the one that has a less-than-ideal background, but has the skills necessary to get the results you want. The answer is quite obvious.

 

So, like education, you should make sure that the candidate has the necessary data science skills and experience for your needs and requirements. If they do, they’ll be able to do the job and deliver results, even without the right background.

 

Soft Skills

 

Education, background, and coding ability all refer to hard skills that a data scientist should have. Many companies, though, often forget the soft skills necessary for the job.One of the most important soft skills can that a data scientist should have is communication. This is not only important because they need to communicate with team members and other stakeholders within a company, but also because they’ll have to communicate the story that data is telling. So, in addition, the candidate should also have the necessary language skills to facilitate proper communication with you, and other stakeholders in your company.

 

They should thus be able to translate what the data is showing into insights that a company or business can use to improve its business processes. As a result, they should be able to distil challenging technical information and data into a form that is easily digestible and easy to present, while, at the same time, being complete and accurate.

 

Another important consideration when it comes to soft skills is making sure that the candidate is a cultural fit for your business. In other words, the candidate should fit into your business’s culture and understand your goals and values. It’s simple, if there’s no cultural fit, the working relationship with the data scientist will simply not work, no matter how qualified they are.

 

The Bottom Line

 

Data is becoming increasingly prevalent in the business world as companies use it to gain valuable insights, which enable them to improve their business processes significantly. To extract these insights from the data, though, they need a data scientist.

 

When hiring a data scientist, it’s important to look at several things like their education and background. Although these are important, it’s far more important that the right candidate has the required coding, data science, and soft skills to do the job effectively.

 

If you don’t want to go through the hassle of hiring a data scientist, you can always look at an outsourcing solution. If you want to find out how or need more information about any of our other services, visit our website or contact us for more information.

 

Sources:

 

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