How to Become a Leader in Data Science

7 Min Read
The demand for skilled leaders in the field of data science is only going to become more urgent as big data and technology continue to expand.

By now, we are all well aware of the omnipresence of big data, science, and technology in the business world. We can’t help but notice the rapid, ongoing developments on all fronts.

As tech plays an ever-increasing role in our daily lives, there’s a commensurate push toward new business models that take advantage of well-managed data and business intelligence. As a result, our collective demand for skilled leaders in the field of data science is only going to grow increasingly urgent.

But what does “leadership in data science” mean?

To put it simply, data is useless by itself. The only thing that gives it value is how it’s used and what insights can be gleaned from it. To extract the maximum value from collected data — either from a financial, strategic, or customer service standpoint — an organization needs a strong, clear goal and a way to reach that goal. That takes vision, and — you guessed it — leadership.

Are you suited to a leadership role?

Do you have the makings of a data science leader?

The good news is, most data scientists looking to move into a leadership role have already mastered the essentials of their field. They typically have technical, mathematical, and engineering skills. The bad news is, there’s an entirely separate skill set for being a leader. Not every data scientist is necessarily well-versed.

Just as with other fields of endeavor, leadership means having certain qualities or expertise. The six leadership skills most commonly regarded as vital are listed below.


Being able to listen, explain, simplify and illustrate sophisticated concepts is especially vital in data science. Communicating with a high degree of precision is all but inevitable for success.


The responsibilities of companies that collect big data and the subject of data ethics is an increasingly important and thorny issue. Just as with any other leadership role, a data science leader must be committed to doing the right thing.


Data science is not an easy field of endeavor. The world of data itself is constantly shifting and evolving. Being able to adapt, overcome, and focus on solutions when problems and changes present themselves is an invaluable leadership skill. A team needs a positive attitude and the courage they need to bounce back, especially when things go wrong.


Vision is one of those buzzwords that come up a lot when people talk about leadership. It can mean any number of things. Mostly, vision is about having a clear goal in mind. It includes knowing the risks and rewards and making sure the rest of your team understands those risks and rewards, too. No one can predict the future. However, having the foresight to see possible challenges — and their solutions — before they present themselves is vital to good leadership.


One of the main functions of a skilled leader is to inspire others. It’s tough to do that without a strong, positive attitude of your own. That doesn’t mean being “sunshine and roses” every minute of every day. However, data scientists, just like everybody else, need some encouragement when the going gets rough.


Another crucial leadership skill is the ability to delegate. By definition, if you become a data science leader, you won’t be able to do it all yourself. That means not only trusting others to do the job you give them, but also providing them with the tools and guidance they need to succeed.

Areas of Data Science

“Data science” is itself a broad term that can encompass a number of areas. Once you decide you want to try to take on a leadership role within your organization, it might be helpful to focus on one of these areas so you can specialize. The more common areas of data science include:

  • Data Management
  • Data Engineering and Architecture
  • Artificial Intelligence
  • Data Science Strategy
  • Data Analytics
  • Business Intelligence and Strategy
  • Research
  • Ethics and Legalities
  • Policy and Governance

How can you become a leader in data science?

Leadership in data science isn’t fundamentally that different from leadership in other fields. It includes skills that can be taught and learned, even if you’re not starting from a point of “natural” leadership or confidence in your personal charisma. Listed below are some quick tips as to how you can begin positioning yourself for a leadership position.

  • Take initiative and be proactive. Present ideas when they come to you. Make yourself available to join projects. Accept opportunities as they come along. In short, make yourself a valuable asset that everybody wants to have around.
  • Improve your leadership skills. Take training courses in communication and team leadership. You might also work with a mentor on these skill sets.
  • Consider acquiring a master’s in data science. Doing so will sharpen your soft skills. You’ll also gain valuable credibility in the industry.
  • Be assertive in networking within the industry. It’s not all “who you know,” but knowing the right people certainly helps.
  • Stay up to date on the latest tech and trends in the industry. That way, you not only know what’s happening right now. You can also look to the future…and that’s what true leadership is all about.
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Becca Williams is a writer, editor, and small business owner. She writes a column for and many more major media outlets.