Data Scientists: The Adventurers and Skeptical Detectives of the Digital Age

Harvard Business Review once described data scientists as having “the sexiest job of the 21st century.” So, what makes this profession so appealing? The title “data scientist” was first coined in 2009 by Nathan Yau, who defined a data scientist as someone capable of extracting insights from large datasets and delivering them in a form accessible to non-experts. In layman’s terms, a data scientist is akin to a hybrid of an explorer charting unknown territories and a skeptical detective questioning every assumption.

In 2005, the National Science Foundation published *Long Live Digital Data Collection: Promoting Research and Education in the 21st Century*, which defined data scientists as “information and computer scientists, database and software engineers and programmers, disciplinary experts, and key figures in successfully managing digital data collection.” In simple terms, data scientists should be multidisciplinary talents who are both scientists and engineers, playing a vital role in business decision-making and innovation. Below, we examine the competencies and characteristics of data scientists as summarized by Thomas H. Davenport (Director of the Accenture Institute for Strategic Change) and D.J. Patil (Science and Technology Policy Fellow at the American Association for the Advancement of Science, serving the U.S. Department of Defense).

CuriosityData scientists possess strong curiosity, driven by a desire to understand the world through data exploration, identify the core of problems, and probe their essence, ultimately distilling these insights into a set of clear, testable hypotheses or conclusions.Problem Analysis and Synthesis CapabilityA data scientist is, first and foremost, a skilled analyst. When confronted with complex problems, they define an analytical framework, formulate simplifying assumptions, leverage appropriate analytical tools to dissect the problem, and ultimately identify solutions. Specifically, data scientists excel at transforming large volumes of unstructured, disparate data into structured, analysis-ready datasets. They identify rich data sources, integrate other potentially incomplete data sources, and clean them into final result datasets. By analyzing these data, they derive conclusive insights.Rapid Learning AbilityData scientists must be adept at rapid learning to address evolving challenges and analyze continuously incoming new data, including ad-hoc data analysis and ongoing interactive data analysis, thereby providing decision-makers with support and actionable insights. As data scientists need to master a diverse set of comprehensive skills, strong learning agility is essential, serving as a core competency for professionals in scientific or engineering roles.Problem Transformation CapabilityData scientists possess strong problem-solving abilities, and therefore also excel at problem reframing. They have the capacity to comprehend and apply knowledge, enabling them to consistently devise novel solutions when encountering technical bottlenecks. This is an essential skill for anyone serving in the role of a scientist or engineer. Proficient in Business OperationsData scientists must master business operations to better serve them, and by exploring data that extends beyond the scope of current business activities, they can also recommend new strategic directions.Demonstrating Communication SkillsData scientists are not only adept at communicating with business professionals and understanding the essence of business to ensure data serves commercial objectives, but they must also excel in creating sophisticated data visualizations. This involves leveraging creative graphical methods to convey information clearly and effectively. Data scientists can articulate ideas and concepts efficiently, striking a balance between design and functionality. Their work avoids being dull due to purely functional implementation, while also preventing complexity arising from excessive visual effects. By intuitively highlighting key aspects and features, they enable deep insights into the data. Decision-Making AbilityThe greatest value of data scientists lies in translating insights derived from data exploration into actionable business recommendations, thereby influencing products, processes, and decision-making to demonstrate their commercial impact. This unique ability to drive business value is what sets them apart from other technical roles and makes the profession particularly appealing. Today, we discussed the characteristics of data scientists. So, how does one become a data scientist? Stay tuned for our next installment.

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