CAREER PROSPECTS FOR SOCIAL SCIENCE GRADUATES

Social science is a popular field of study around the world, due to its diverse range of subjects, fascinating research topics, and its ability to influence policy and society. Nearly 4 out of 10 students graduate university with a social science degree in the UK and social science is the third most popular field for bachelor’s degrees in the US.

Today, the career prospects of social science graduates are bright, with employment rates similar to STM graduates according to the Campaign for Social Science’s Positive Prospects 2018 report. In fact, the BBC reported that social science graduates are more likely to find employment and to have a managerial or senior role than those who studied arts or science. This comes as no surprise as the transferable analytical, critical thinking and research skills gained in social science degrees are attractive to employers across sectors – not just for social science jobs like political scientist, economist or organizational psychologist.

However, the rise of big data is changing the world around us and, consequently, shaping the future workforce. While the skills gained in traditional social science degrees are still valued by employers, it’s becoming increasingly important to have numeracy, data literacy and quantitative skills to succeed.

This raises the question of what will the future successful social science graduate look like? And what skills must universities equip with students with to ensure their employment prospects flourish in the data revolution?

DATA REVOLUTION: DEMAND FOR QUANTITATIVE AND DATA SCIENCE SKILLS

You’ll have heard the stat thrown around that 90% of the world’s data has been created in the last ten years. In fact, according to DOMO’s 2018 Data Never Sleeps Report; ‘over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth’.

However, working with big data requires new software tools, data science skills and quantitative and computational methods. Brendan Burchell from the University of Cambridge pointed out that:

“Over the next few decades… we are likely to see huge advances in the use of quantitative data including datasets that can only be analysed with big data techniques.” 

As a result, there’s been a rise in the number of jobs needing advanced quantitative skills, with 7 in 10 UK employers saying quantitative skills are essential to their jobs. And this is not just the case for the UK, there’s been rapid growth in demand for data science and programming skills from employers around the globe (IBM, 2017).

SO, WHAT DOES THE FUTURE SOCIAL SCIENCE GRADUATE LOOK LIKE?

This explosion of big data is revolutionizing both social science research and the job market. For research, it provides an opportunity to address existing questions in different ways and pose entirely new questions. For the wider job market, there’s been a shift to data-driven decision making and evidence-based policymaking.

To thrive in this data and digital-driven environment, the future social science graduate will need to be able to work with very large datasets. This means knowing how programming languages and being comfortable with statistical software packages, such as R, that can handle big data.

Graduates continuing in research will need to know new computational methods (like machine learning or quantitative text analysis), have new skills (like web scraping) and work with new tools (such as APIs) to research topics like online hate speech, the role of social media in influencing voting behavior, fake news and more.

In short, the future successful social science graduate needs to have enhanced data science, data literacy and quantitative skills, on top of their general analytic skills and knowledge of society.

CHALLENGE FOR INSTITUTIONS: GIVING GRADUATES FUTURE-PROOF SKILLS

This presents a challenge for institutions, as analyzing big data requires new data science skills and computational methods that aren’t often taught in traditional social science degrees. And there’s been evidence that despite social science students increasingly using big data for research, their data science skills fall short of what is required.

To address this, several high-profile capacity-building initiatives, such as Nuffield and the ESRC’s Q-Step initiative in the UK, have been launched in recent years with the aim of improving the quantitative research skills of postgraduates and undergraduates.

However, institutions still have a way to go. Faculty members may not have the skills themselves to teach students, and rarely have enough time in the curriculum to teach notoriously tricky and time consuming social research methods and data science skills. Furthermore, students from different disciplines can have widely varying technical abilities, which makes teaching in limited face to face hours challenging.

Institutions can look to use supplementary materials for a flipped classroom approach to address these challenges and ensure students practice in their own study time and cover mastery and application in class. Online courses are a good resource for providing practical examples that are needed for mastering skills like programming, which students simply can’t get from books.