Thomas Davenport, visiting professor at Harvard University and author of the watershed book Competing on Analytics, is once again making waves across the datasphere with his proclamation of data scientist as the “sexiest job of the 21st century.”
To many readers here at the Perspectives site, of course, this is not news, as many data professionals have increasingly been recognizing – and are being recognized – for the increasing power of information in driving new insights and business opportunities.
However, there’s more and more chatter about this new role of “data scientist.” Who, exactly, is this person? Is it a rebranded business analyst? For his part, Davenport defines the position as “a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data.”
So, data scientists are the new breed of professionals tasked with making business sense out of Big Data. As Davenport explains it, the demand for these professionals is far outstripping supply – a reflection of the relentless growth of data across organizations of all types and in all industries.
What skills are needed to either nurture, or even become, a data scientist? The job description itself is still evolving, but Davenport offers some basic areas of concentration:
- IT and programming skills: Able to develop prototypes in a mainstream programming language such as Java.
- Statistical skills: A solid foundation in math, statistics and probability.
- Business skills: This separates data scientists from traditional “quants” as we’ve known them. Data scientists need acumen in business issues and “empathy for customers,” says Davenport. The data scientist plays a role in the business as a consultant, who likely will meet regularly with top-level executives.
- Intense curiosity: This is probably the most important skill or trait, Davenport says. It includes “a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested. This often entails the associative thinking that characterizes the most creative scientists in any field.”
Don’t be misled by the word “data” in the job title, Davenport adds. “A quantitative analyst can be great at analyzing data, but not at subduing a mass of unstructured data and getting it into a form in which it can be analyzed,” he says. “A data management expert might be great at generating and organizing data in structured form but not at turning unstructured data into structured data—and also not at actually analyzing the data. And while people without strong social skills might thrive in traditional data professions, data scientists must have such skills to be effective.”
What are companies looking for these days from this new emerging job role? Here are some examples, culled from online job site SimplyHired.com. Note the strong emphasis on business and management skills:
- Government contractor: “A self-starter with demonstrated experience using SAS and SQL programming; as well as possess strong experience developing, implementing, and maintaining predictive statistical models using modeling techniques including but not necessarily limited to logistic regression, survival analysis, neural networks, and decision trees. Excellent interpersonal skills, and professionalism and self- awareness; as well as the ability to communicate comfortably with all levels of staff and management are a must.”
- Business services company: “Analyze and optimizes customers’ multi-tier, multi-channel digital marketing programs. Successful analysts are able to think strategically about business issues while, at the same time, dive into the data. They must-have a strong command of digital marketing and advertising concepts. Key responsibilities include advising enterprise clients and agencies about large-scale advertising analytics and optimization. We are looking for a true ‘Data Detectives.”
- Government agency: “Technically-savvy specialists to organize and interpret Big Data to inform US decision makers, drive successful operations, and shape agency technology and resource investments. Work with advanced hardware, software, and techniques to develop computational algorithms and statistical methods that find patterns and relationships in large volumes of data. Have keen technical insight, creativity, initiative, and a curious mind. Data Scientists will be expected to communicate their conclusions clearly to a lay audience and become experts through continued education, attending academic and technical conferences, and collaboration with the agency’s community.”