The 7 Habits of Highly Effective Data Scientists

Data Science is not just one technology. It is a revolution in the world of information technology which includes several languages and technologies. If you are called a data scientist, you will be expected to have significant knowledge about Artificial Intelligence, Data Mining, Data Analysis, Deep Learning, and many others. This boom of data science has been an encouragement for people in the field of computer science and information technology, to learn and gain expertise in it.

At the time of hiring, how would you differentiate between the multiple data scientists that which one is better than the other because, on paper, they are the same? They are working on the same technology and having more or less the same skill set. The way that you can judge whether or not they have are up for the data scientist vacancy you need and will be an excellent addition to your organization, is to ask for their habits and expect them to have specific answers to that question. Those responses will somewhat give you the entire picture, whether or not they will be a valuable addition for your organization. These are some of the commonalities found in the habits of data scientists

Improvise and Experiment:

The data scientists like to explore possibilities by doing things differently. They want to be out of the box thinkers in not only IT-related tasks but in usual life activities. This a habit which helps them in achieving complex tasks that come their way. Their objective is to make the given task through whatever improvising and experimentation they want, and hand it over to the quality assurance personnel, for pointing out any sort of errors or things that need to be changed.

Knowing the Script:

It is okay for a data scientist to be mastering the current technology with extreme proficiency, but they have one eye on the future. They are quick to know about any technological trend that has changed or any new technology that is announced, and adapt themselves accordingly. Just like the IT industry, data science is also continually evolving. When it does, it would be insignificant whatever you have achieved, the one who adapts to changing technology will be the industry leader.

Networking:

Having already mentioned that data scientists have one eye on future technologies. One way to do this is having the right type of people around you, who will contribute to your professional development. The benefits of doing so do not limit to this. It goes way beyond like opening better career opportunities, supporting in any task that you might find challenging, and expend the thinking capacity with positive and realistic conversations. One way to do so is to see whether or not they attend these meet-ups and events for data scientists.

Good Reader

Being a data scientist does not mean it’s all about coding and learning programming languages. It is also about getting the knowledge about your industry and profession. To achieve this purpose, you need to select reliable reading resources to educate yourself. This can be blogs, magazine, communities, and much more. The more knowledge you have about the industry, apart from your technical skills, the better you will chances you have to stand out from a person with similar skills than you.

Independent Learning

Learning data science or anything for that matter depends on the will to explore different avenues to enhance your skills of data science, beyond any degree, course, job, or whatever you are doing. There is virtually no limit to how much can you learn if you have to passion and the urge to do it and keep building on the list of technical and professional skills you have. Whichever new market trend or technology you get to know about, try it out yourself, to whatever you understand.

Experience means everything

Most of the people who want to acquire the services of a data scientist for employment purposes, go beyond than just what is educational achievements they have and what have they learned. They focus more on the personal experience they have about how they have used their leanings that would highlight their ability to achieve complex tasks through their problem-solving skills.

Willing to Assist

It is a trait in data scientists that they are open to help any data scientist which their particular task, in the capacity that they have. You can find an example of this in the platforms like Quora and Github. You will see a clear picture of how open and ready to help the data scientists are, by not only being prepared to answer with sharing their experiences and leanings about your query but sharing entire source codes for executing specific tasks. This will not only be expending the data science community but extending your name in the industry, as an efficient data scientist.

Conclusion:

Data Science is not as established and recognized as some of other Computer Science technologies, yet upon its arrival, it has taken the world by storm. There is a large chunk of the world population that have entered this industry and have the desire to excel. This is a new technology that organizations need to understand and use this technology effectively by hiring the right personnel. Many pre-requisites need to be achieved, and you can find multiple online and physical courses and certifications that are available for you.