6 Traits of a bad data scientist
You may already know about the things you should look for in a data scientist, but here we have formulated a list of the traits that are a complete no-no. Get this – you are going to trust your data scientist with your company’s confidential data. You expect him to not only source the data, but also analyze it to come up with insights that can help you predict future scenarios. The outcome of the predictive analysis is most likely to help you plan your future endeavors.
So, in order to find someone who is capable enough to shoulder this huge responsibility, you need to have a full proof plan in place. It is definitely important to hire a data scientist who is good at this, but it is equally important to ensure that you do not end up recruiting the wrong person.
Look for the warning signs mentioned below before you make your decision. You can thank us later.
1. Not a good mathematician:
An in depth knowledge of mathematics or statistics is a prerequisite for becoming a data scientist. Your candidate should be capable of building mathematical models using the available data to help you achieve your goals.
Only a good mathematician or statistician will be able to understand and learn the algorithms to carry out accurate predictive analysis. Thus, a strong academic background in this subject is nothing less than a necessity.
2. Does not have a scientific outlook:
A data scientist needs to have a scientific mindset when it comes to experimenting with the available data, hence the job title. He is bestowed with the task of making sense of a vast amount of data and a scientific approach can simplify the process by a large extent. So, if you sense a lack of this important trait in your candidate, you know what you need to do.
3. Weak programming skills:
One of the reasons why data scientists are lovingly called the unicorns of the industry is that they need to be pretty good at programming, apart from excelling in mathematics. We are not saying your data scientist should have an exceptional computing knowledge, but basic programming skills are a must. He should be able to change the code if need be, in order to manipulate the data to get optimum results.
However, make sure your candidate’s knowledge is not restricted to SAS. He should be capable of not only writing the code, but also analyzing the available data.
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4. Bad communication skills:
What is the point of hiring someone who is excellent at analyzing the data, but unable to explain it to the lesser mortals who can’t understand mathematical models or algorithms even if their lives depended on it? Basically, your data scientist will have to explain the outcome in simple terms and successfully get his point across to those who deal with all the other aspects of your company. Some fine storytelling skills wouldn’t hurt either.
On the other hand if you require your data scientist to design autonomous computer programs by leveraging the principles of machine learning, then look for someone who is well-versed with the tools that are primarily used for the purpose. A working knowledge of technologies such as SAS, Python, Scala and R to name a few, should definitely be a prerequisite in this case.
5. Poor business analysis capabilities:
Even if your data scientist is an excellent mathematician, great at programming and knows how to communicate, he is still not the right person for the job, if he cannot help you apply his findings for the betterment of your business. Ultimately, your goal of hiring a data scientist is to broaden your horizons in the industry by using the acquired insights. Therefore, it is absolutely necessary for your data scientist to have basic business analysis capabilities.
6. Lack of motivation:
No matter how exceptional your prospective candidate is, if he does not possess the drive to learn something new or come up with groundbreaking insights, he cannot become an asset to your company. He needs to have an inherent sense of curiosity to push him to get outcomes and results which will be beneficial to the company. If a data scientist lacks motivation, he is not very likely to excel at his job.
Let’s not forget that your data scientist also needs to follow the code of conduct laid down by the Data Science Association. It goes without saying that he should be a reliable employee, a team player and have brilliant researching skills as well.
We sincerely hope that this list will help you in your screening process while recruiting the perfect candidate. But if you are still unable to find the right person, simply hit this link.