Five Must-Have Characteristics of Extraordinary Data Scientists

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characteristics of data scientists
Read more about author William Skelly.

There’s no better time than right now to be a data scientist.

Despite recent large-scale layoffs in major tech firms, the future is bright for data managers, analysts, data wranglers, and consultants. In fact, the number of jobs requiring Data Science skills is expected to grow by 27.9% by 2026, according to the U.S. Bureau of Labor Statistics.

Continuing advancements in technology and big data mean career opportunities for data scientists will remain in high demand. Add the rapidly evolving areas of artificial intelligence (AI), machine learning, and blockchain, and the role of data scientists will expand to include risk management, data governance, ethics, data visualization, and more.

Skill Sets for a Career in Data Science

Typical skill sets required for a career in Data Science include being analytical and detail-oriented and possessing linear thinking. Being curious and inquisitive, while aligning with the scientific method, is also important.

As more organizations lean on data to make strategic business decisions, keep loyal clients, and acquire new customers, data scientists are being challenged to enhance their knowledge and experience. Some data scientists may choose to specialize in a specific area, such as business and market analytics, AI and machine learning technology, or infrastructure and data cleansing.

Characteristics of Extraordinary Data Scientists

As corporations and organizations across the globe require data that is vaster and more varied than ever before, the most successful data scientists will be those who possess characteristics outside the norm. These data experts will excel beyond the typical left-brained demeanor (i.e., logical, analytical, and orderly thinking). Exceptional data scientists will also embrace right-brained behavior, which is more creative, artistic, and imaginative.

Here are five characteristics of extraordinary data scientists:

1. Blue sky thinkers

With accelerated AI innovations, mercurial media platforms, and emerging high tech, blue sky thinking is necessary to solve today’s problems and the unforeseen challenges of the future. Data experts must contribute to productive brainstorming and adopt an inventive mindset to help their organizations address volatility in the global economy, political uncertainties, and more. 

2. Prioritize application over education

So-called “book smarts” create a strong knowledge base for new data experts, but oftentimes those lessons are rigid and don’t apply to the unstructured questions being asked in real-world scenarios. Furthermore, the evolution of the field is happening so quickly that tools and techniques learned in school are obsolete they are put into practice in the workplace. Even computers from a few years ago are now considered antiquated. Being street-smart may be better than being book-smart right now. While a college degree will always be important, data scientists must also be ready to unlearn, relearn, and upskill to tackle unexpected hurdles. Data experts are advised to regularly update their certifications, take courses on the latest software, and get training on system upgrades.

3. Convert complexity to simplicity

Data scientists must be ready to work with colleagues across departments who are unfamiliar with data and the technology being used. They need to explain the terminology and acronyms and simplify language so that teammates will understand the value of the numbers and information being provided. By simplifying the complex, data scientists enable teams to be more collaborative and meet the organization’s goals.  

4. Visual storytellers

Using data visualizations helps executives and other team members clearly establish the value of the information being provided and supports data-driven decisions. Organizing datasets into a story aligns decision-makers and streamlines action steps. Savvy data scientists will partner with marketing or design experts to create data visualizations and craft a compelling story.

5. Take a consultative approach to problem-solving

In a highly competitive environment, gone are the days when data scientists can simply provide mountains of data and then walk away thinking it was a job well done. It’s true that it is a monumental task to organize, cleanse, and analyze the data, and then create a report complete with spectacular visualization. But now, data experts must also work with teammates across the organization, taking a consultative approach to problem-solving. Data scientists must consider the bigger picture and overall organizational goals. They must serve as an asset in overcoming obstacles, helping to gain market share, increasing sales, and more.

These five characteristics underscore the changing role of data scientists. Although today’s data scientists may be asked to stretch beyond their comfort zone, by embracing these qualities, they’ll be among the extraordinary data scientists who will be invaluable to their organization.