3 Undervalued Data Science Skills You Should Learn

Author: Staff

Aerial view of a woman sitting at a table typing on a laptop.

Early in 2018, Data Scientist Caitlin Hudon tweeted an important question: What is the most underrated or undervalued skill for a new data scientist?

When we think about the important skills for data scientists, many of us immediately think of their programming and quantitative abilities.

While these skills are crucial for developing the technical foundation of the data scientist skill set, the “soft,” non-technical competencies can make a data scientist even more valuable to their organization.

Today’s new data scientist needs to be:

  • Adept at data storytelling
  • Attune to issues in data ethics
  • Able to work in teams

Skill #1: Be Adept at Data Storytelling

Data scientists are set apart from other data professionals by their ability to communicate data analysis into actionable insights that technical and non-technical audiences can understand.

A key point we stress in our 5 Trends Shaping the Rise of the Three-Dimensional Data Scientist white paper is the need for emerging data scientists to communicate their insights through data storytelling:

“Data scientists cannot just apply algorithms to information; they must also have the skills to contextualize this information for different audiences and to communicate effectively. The most effective data scientists are talented storytellers, clearly communicating their analytical insights in order to enable organizational decision-making.”

Dr. Jennifer Cronin, a member of our data science faculty, further reiterated why data storytelling is a critical skill for data scientists:

“The most robust data and statistical analysis isn’t going to matter if you’re not able to communicate the impact of the data you uncovered in a compelling way.”

This aligns with research from McKinsey Global Institute suggesting that a major contributor to the data science talent shortage is the lack of skilled storytellers or “business translators” who are able to describe what the data reveals in a way that supports business decisions.

Furthermore, the industry leaders we spoke with reiterated the same answer about the top data science skills for future data scientists.

“Exceptional communication skills” was consistently high on their list.

What is the bottom line?

As companies and organizations look to create value from data, future data scientists can better position themselves for career success by mastering the art of data storytelling.

Our online master’s in data science program integrates storytelling throughout the curriculum to prepare students to be talented storytellers, who can clearly communicate insights to technical and non-technical audiences.

Skill #2: Be Attune to Issues in Data Ethics

At a time when algorithms influence so many decisions in our lives, it’s imperative that new data scientists not just master the tools of the trade. They must also be grounded with a strong ethical framework that helps them analyze the ethical implications of their work.

The ethical perplexities emerging data scientists must navigate is another major point we address in 5 Trends Shaping the Rise of the Three-Dimensional Data Scientist:

“Awareness of ethical questions, familiarity with regulatory frameworks, and the tension between business drivers and privacy rights creates an ongoing struggle for the data scientist, one that begs for clarity and resolution.”

Here is a great example why:

Just a few months ago, a BBC News article showed how even a straightforward tool, the Strava Fitness App, illustrates the ethical concerns about data privacy and the unintended consequences for those working without a data code of ethics.

Strava has a feature that shows a heatmap of a runner’s and other runners’ (or bikers’) routes:

 

Image via Strava

What Strava didn’t realize is that, in making this data public, the heatmap exposed military bases, which bases are used most often, and the routes taken by soldiers at these bases.

The unintended consequences to national security could have been prevented or significantly mitigated if decision makers had been informed by or followed a better data protocol before releasing the information.

There is a critical need for data scientists who are prepared with a strong ethical foundation and who understand the questions to ask and the framework to analyze ethical concerns.

It’s not enough to ask, “Can we?” The critical question must be, “Should we?”

Since ethical decisions are not always easy or clear-cut, the best leadership and guidance in this effort will come from data scientists who have gained a solid grounding in the issues related to the proper roles of public law, government regulation, and ethics in performing and managing analytic activities.

At Notre Dame, we are committed to training ethical thinkers and data science practitioners who will be leaders in the field and play a significant role in crafting the profession’s ethical framework.

Skill #3: Be Able to Work on Teams

The notion that data scientists are holed-up in their offices crunching numbers and building algorithms apart from the rest of the business or organization is contrary to the true role a data scientist plays.

A data scientist cannot exist in isolation.

Today’s talented data scientists are resourceful, work on diverse teams and engage in back-and-forth iteration with team members in business, IT, and sales and marketing, as well as the president and CEO.

Shane McCarthy, Senior Software Engineer at Uber, acknowledged that the ability to work with diverse teams throughout an organization is an essential skill for future data scientists to master.

“I have the most appreciation for the data scientist whose insight is derived from partnerships on the team. What I mean is, they understand the implementation from a higher level, know how we implement our products from the software engineer’s perspective, and partner extremely closely with our product manager to be able to talk about the products as well as anyone. They also partner with the data engineers to further optimize their pipelines.”

Given the importance of teamwork for success in data science careers, the group work in our online master’s in data science program is designed to mirror a typical work environment for data scientists.

Learn more about how Notre Dame’s online master’s in data science prepares its graduates to be exceptional storytellers, to understand and apply ethics in data science and to be valued team members in 5 Trends Shaping the Rise of the Three-Dimensional Data Scientist.