How to hire a good Data Scientist
As with any high quality hire, it takes a lot of time and effort to hire a good data scientist. Knowing if they are a good fit for your organization is key to help your company make the leap into this field.
We’ve already discussed the surging demand for data scientists. It’s only expected that the best ones are considering several options and figuring out which company offers the best opportunity for growth. However, you as the employer need to know that the candidate you are considering to hire is indeed the one.
We developed a short list that you might need to ask in order to figure out if this person is right for the job, or not:
- Does he or she have great programming skills? Data collection techniques, such as web scraping, required good coding chops. Also, even though the data scientist doesn’t have to implement common algorithms from scratch (K-Means, Regression Analysis, etc), it helps if they have a good understanding of the fundamentals in case they run into code related obstacles.
- Is he or she a good communicator? The need to communicate processes and results in layman terms is a basic skill required for this job. After all, data scientists need to tell a story through data and use visual communication tools to do so.
- What’s the state of his or her business understanding? If the candidate in question understands how data affects profitability and user experience among other valuable variables for a business, he or she is on the right track to become a coveted asset in your company. If the candidate has some background in business, the better he or she will spot trends that benefit you.
- Can the applicant give you concrete examples of when he or she improved a business? See question number 3. It will add some extra points if you can pinpoint real-world examples of his or her business knowledge and experience.
- Does the applicant have a scientific mind-set? Many amazing data scientists come from fields such as astronomy, physics, bio informatics, and economics, just to name a few. These disciplines emphasize the scientific method and are core skills required for productive data scientists.
Last but not least, the candidate should be able to apply the scientific method to data, meaning he or she is willing and knowledgeable enough to experiment with it. Being curious and following a method will help the prospect come up with specific real-world models catered to your business.
These are only some of the things that you might want to consider when hiring a data scientist. If the candidate has these five qualities then you are standing in front of a strong and capable contestant suited for the position.
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