• Alastair Majury

Habits of Successful Data Scientists

Data science is a rapidly growing field and is proving to be one of the hottest fields of the twenty-first century. As more people are transitioning into data science either as professionals or students piquing their interest, data science consequently becomes more competitive. Beyond knowledge and skills, there are a few habits that data scientists should practice to be more effective and give them a competitive edge.

Experience is arguably more important than education to prospective employers, as it gives them a more accurate representation of a data scientist’s capabilities. Practical application is the true test of knowledge and is honed through experience. Data scientists need to be able to solve complicated problems as data grows more complex. What’s the best way to gain more experience if you are trying to break into the data science industry? Develop and expand your portfolio by seeking out projects. It should be mentioned that companies may overlook resume bolstering qualifications in favor of a portfolio and experience.

An important quality of a successful data scientist is the willingness and readiness to collaborate. There are ways to be active in the community even outside of the office. There are a number of forums that exist on the internet where data scientists post their queries; one of the more prolific platforms is Quora. To get involved, one can proactively search for questions and answer them. In doing so, not only are you helping the community, but it helps to elevate you as a competent data scientist.

In addition to collaboration, networking is another particularly useful habit of successful scientists. These connections bring value to both the community as well as your career. Staying connected keeps you informed of industry trends especially as things are constantly changing. Networking is invaluable to career growth because it likely opens up opportunities. One of the best ways to network is to do it in person by attending events like conferences.

Data storytelling is an underrated yet highly effective habit to practice. More often than not, your audience will not be fellow data scientists. Data storytelling goes beyond the numbers and analytics to extract value and insights from the data. The storytelling aspect simplifies the figures as well as adding interest for an audience that may be less data-literate. A strong narrative gives the decision makers the clarity to better understand the appropriate action that needs to be taken.

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