Why study MSc Data Science at SOAS? Technical training with Global South perspectives
A closer look at SOAS’s MSc Data Science programme, combining practical coding and analytics skills with critical insight into how data and AI shape real-world societies.
Data science is reshaping every sector, from finance to public policy. At SOAS, the MSc Data Science programme takes a distinctive approach - combining hands-on technical training with critical global perspectives on how data and AI shape societies. We spoke with Anuja Bajaj to learn more about what makes the programme unique.
What makes MSc Data Science distinctive?
The MSc Data Science is distinctive in combining rigorous, hands-on training in modern data science (including statistical methods, machine learning, big data analytics/AI, data management and visual analytics, and programming in Python and R) with SOAS’s Global South perspectives.
The programme explicitly emphasises context-sensitive, ethical data practices grounded in diverse epistemologies and developmental priorities, and it encourages students to conceptually interrogate ways in which AI technologies are embedded in colonial-imperial practices of digital extractivism, labour exploitation, and knowledge-production hierarchies.
Conceptually interrogate ways in which AI technologies are embedded in colonial-imperial practices of digital extractivism, labour exploitation, and knowledge-production hierarchies.
The programme also offers optional modules that connect technical skills to public-facing and cultural domains (e.g., data visualisation/storytelling and data journalism), and a substantial research project to apply the concepts learnt.
Who will the course appeal to?
It will appeal to students who want to build strong data science capabilities while applying them to economic, political, social, and developmental questions, including those from a wide range of disciplines (the programme considers applicants from any discipline that doesn’t already include a strong data science component). It’s particularly well-suited to people who want both practical coding/analytics skills and a critical understanding of what data and AI do in real societies.
What transferable skills will students learn?
Students develop highly transferable analytical and technical skills, such as coding in Python and R, working with real-world datasets, data acquisition/cleaning/structuring, reproducible workflows, interpreting and communicating results through visual analytics, and applying machine learning methods appropriately. Just as importantly, they build critical judgement around responsible and ethical use of data science/AI across different contexts.
What types of careers do graduates progress to?
The programme is designed to support careers in businesses, financial institutions, government agencies, non-government organisations, and international organisations. It is especially suited to roles requiring coding skills and the ability to apply data science methods with an understanding of their implications. It can also serve as a strong foundation for PhD study for those who want to pursue research pathways.
Is there a Study Tour linked to the course?
Yes, all SOAS postgraduate students can take part in SOAS Study Tours, with recent destinations including New Delhi, Lahore, Seoul, Luang Prabang, Almaty, Bishkek, Kigali, Johannesburg, and Doha.
What are some of the current key debates in Data Science?
A few big debates shaping the field right now include: (i) how to ensure data science and AI are ethically deployed (especially where data are scarce or unevenly produced), (ii) algorithmic bias and fairness, (iii) transparency/interpretability versus predictive performance, and (iv) the political economy of data that discusses who collects it, who benefits, and how models can reproduce existing power asymmetries.
Students will discover ways in which many AI engines themselves structurally reinforce the kinds of social and economic inequities produced by racial capitalism.
The course engages these issues directly through its compulsory module, ‘Critical Global Perspectives on AI and Ethics’. Drawing on interdisciplinary expertise across the College of Humanities and parts of the College of Social Sciences, students will discover ways in which many AI engines themselves structurally reinforce the kinds of social and economic inequities produced by racial capitalism.
Students will also engage with how AI technologies influence personhood, memory, communication, translation, and cultural preservation, and labour, thereby directly confronting how ever-growing AI technologies may either reinforce or challenge contemporary social inequities.
What are some of the real-world applications of Data Science?
Data science methods are now routinely used in policy analysis, economic and financial forecasting, public service delivery, labour market analysis, media and communications, and large-scale text/social media analysis, as well as in organisational decision-making in business and the non-profit sector. The programme is explicitly hands-on, using real-world datasets and applications to build confidence in applying methods rather than only learning them in the abstract.
Can data science help to alleviate some of the world’s development problems?
Done well and sensitively, data science can improve how we understand and respond to development challenges, for example, by identifying patterns in inequality, recognising a range of structural injustices, evaluating programme effectiveness, improving targeting of resources, or modelling risks and vulnerabilities.
The course places strong emphasis on context-sensitive practice, ethical considerations, and critical evaluation of what data can and cannot capture, particularly in Global South settings. This combination helps students use data science as a tool that supports developmental priorities and social justice goals.
