5 Signs That You Are NOT a Data Scientist
Data Scientist is why don't you, and the rock star job title of the second? There is a very big demand plus a very small pool of qualified candidates.
But just since you aspire to be a data scientist doesn't mean you are qualified to be one. Here are a couple signs you're not qualified for that unicorn occupation yet:
You do not have the abilities that are advanced. One study of data scientist wages found that 88% of data scientists have at least a Master's degree, and 46% have a Ph.D. The areas change from even economics and operations research, computer science to engineering, or math to data. However, the truth is that without the training of an advanced degree, it is incredibly rare for someone to have the practical skills required to be a data scientist.
You come from strictly a research or academic background. All that said people that only have expertise in the academic world, about advanced degrees must work on developing their business acumen. The best data scientists will have the ability to relate the data that is absolute to the real-world business applications.
Excel is your main evaluation software. If Excel is your workhorse, you could be working with data, but you're not a data scientist. But you probably knew that. On the other hand, knowing just how to work with Hadoop, Python, and AWS does not guarantee that you're right for the job unless you can back up that with examples of experience with data that is unstructured.
You do not add anything to the information. For me, the main quality of a data scientist is the capacity to add value through interpretation and investigation to the information. A great data scientist will soon be able to present those facts along with interpretation and visualization which will help the executives and make decisions that are significant and non data scientists in the organization make sense of it.
Nevertheless, originality is a key trait for a good data scientist because ultimately, you're a storyteller. Data is not useful without context, and it is the data scientist's job to provide context and reveal the way the data can help solve problems that are complex.
Naturally, if any of these applies to you, it doesn't mean that you will never be a data scientist, merely that you're not there yet. There is actually no such thing as an entry level data scientist, but there are any number if you concentrate on building the skills that are right of jobs that may lead to a lifetime career in data science.
Data Scientist is why don't you, and the rock star job title of the second? There is a very big demand plus a very small pool of qualified candidates.
But just since you aspire to be a data scientist doesn't mean you are qualified to be one. Here are a couple signs you're not qualified for that unicorn occupation yet:
You do not have the abilities that are advanced. One study of data scientist wages found that 88% of data scientists have at least a Master's degree, and 46% have a Ph.D. The areas change from even economics and operations research, computer science to engineering, or math to data. However, the truth is that without the training of an advanced degree, it is incredibly rare for someone to have the practical skills required to be a data scientist.
You come from strictly a research or academic background. All that said people that only have expertise in the academic world, about advanced degrees must work on developing their business acumen. The best data scientists will have the ability to relate the data that is absolute to the real-world business applications.
Excel is your main evaluation software. If Excel is your workhorse, you could be working with data, but you're not a data scientist. But you probably knew that. On the other hand, knowing just how to work with Hadoop, Python, and AWS does not guarantee that you're right for the job unless you can back up that with examples of experience with data that is unstructured.
You do not add anything to the information. For me, the main quality of a data scientist is the capacity to add value through interpretation and investigation to the information. A great data scientist will soon be able to present those facts along with interpretation and visualization which will help the executives and make decisions that are significant and non data scientists in the organization make sense of it.
Nevertheless, originality is a key trait for a good data scientist because ultimately, you're a storyteller. Data is not useful without context, and it is the data scientist's job to provide context and reveal the way the data can help solve problems that are complex.
Naturally, if any of these applies to you, it doesn't mean that you will never be a data scientist, merely that you're not there yet. There is actually no such thing as an entry level data scientist, but there are any number if you concentrate on building the skills that are right of jobs that may lead to a lifetime career in data science.