By Dr Chris Dowsett, Head of Marketing Analytics for Instagram
I’d like to introduce you to a lesser-known field of insights professionals called Computational Social Scientists.
Every business could benefit from hiring Computational Social Scientists but few people know exactly what that means. So I wanted to try and shine some light on this field.
Full disclosure — I put myself in the computational Social Science bucket so I’m biased. But hear me out, I think you’ll come to appreciate the field.
Computational Social Science boils down to Social Scientists using data processing and data science computation tools (think R, Python etc) to analyze data about people and relationships.
The difference between a computational Social Scientist and a Data Scientist is that the Social Scientist is an expert in studying human behavior and finding patterns in data about population groups.
Social Scientists come from different streams but the major groups include Economists, Anthropologists, Sociologists and Psychologists.
A Data Scientist on the other hand typically leans toward a deep knowledge of both statistics and data computation. Data Scientists typically have statistics, mathematics, computer science and data engineering backgrounds.
That’s not to say one is better than the other. They’re complementary.
A Data Scientist would be your go-to person when wanting to track large volumes of data, run algorithms and develop complex machine learning models at scale.
A Social Scientist would be your go-to person when you want to understand: populations, segments of users or behavior patterns. They use data science tools in a similar way to a Data Scientist, but they look to explain trends in the context of social behaviors.
The Data Scientist brings a deep knowledge set in computing and statistics while the Social Scientist brings a deep knowledge set in patterns related to groups of people. Therefore, the partnership of these two skill sets could be the key to unlocking immense value in large swaths of data.
For example, I recently teamed up with Data Science colleague to present data on banking patterns. The Data Scientist focused on forecasting trends in aggregate across countries and product groups. I focused on how machine learning helped us identify clusters of customers and how data showed the customer groups were motivated to action by different values like price or service or rewards points. In concert, these two viewpoints provided a rich overview.
Most businesses focus on hiring two groups of data insights professionals: Data Scientists and Researchers/Consumer Insights.
I would argue there’s a third important group that are the Computational Social Scientists — professionals with the technical skills to process large amounts of data and the knowledge set that helps them identify behavior patterns among groups of people.
There’s more emphasis on digital social connections and more data available to track behavior than anytime in history. This makes for a promising environment where Computational Social Scientists can help progressive businesses find nuggets of data on behavior and group relationships.
All of this shows that a Computational Social Scientist could be your next best hire.
This post originally appeared on Towards Data Science.
About the author
Dr. Chris Dowsett has been a leader in Analytics for over a decade, with extensive work experience in North America, Europe and Asia Pacific.
He specializes in understanding organizational impact and biases affecting data use, as well as building easy-to-use analytical tools that enable better business decision making and outcomes.
He is currently the Head of Marketing Analytics for Instagram, a Facebook company. Dr. Dowsett holds a Doctorate from The University of Southern Queensland (Australia) and currently lives in Silicon Valley, where he continues his quest to find the perfect smoothie.