MSc in Social Data Science

The growing field of social data science sits at the intersection of data science approaches to information retrieval, modelling, and prediction with social science approaches to theory-driven analysis, critiques of social processes, and linkages between policy and practice. The Social Data Science degree seeks students with training or a demonstrable aptitude for social science work and programming to refine and extend their skills through the generation, analysis, and critique of large-scale social data. The tools for such an approach are multifaceted and evolve quickly. Our programme embeds recent machine learning approaches to prediction, scalable strategies for ingesting and managing large scale data, analytical statistics for explanations, and specialist approaches such as computer vision, natural language processing, and network science. As a social science degree these approaches are generally applied to questions of social scientific relevance such as social inequality, censorship, hate speech, cohesion, and wellbeing.
 

Students will be expected to spend around 40 hours studying each week during term, and to undertake further study and complete assessments during termly vacation periods. During Michaelmas and Hilary Terms, MSc students are advised to allocate between 10 and 15 hours each week for each course they undertake.

Degree-level qualifications
 

As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:
 

• a first-class undergraduate degree with honours in any subject.
   

In exceptional circumstances, applicants with a distinguished record of workplace experience or other relevant achievements may be accepted with lower grades at undergraduate level. We nevertheless strongly encourage any applicants from industry to include at least one reference from an academic or someone in academic-related field.
 

For applicants with a degree from the USA, the minimum GPA sought is 3.7 out of 4.0.
 

GRE General Test scores
 

No Graduate Record Examination (GRE) or GMAT scores are sought.
 

Other qualifications, evidence of excellence and relevant experience
 

Applicants are normally expected to demonstrate quantitative aptitude or experience in introductory calculus and matrix algebra, equivalent to, for example:

• A-levels mathematics

• Mathematical Studies SL from the International Baccalaureate Diploma Programme

• or Advanced Placement (AP) Calculus AB.
   

Applicants may demonstrate this aptitude/experience in a variety of ways including:

• undergraduate transcripts with a strong pass for Probability, Statistics, Linear Algebra, and/or Calculus;

• an A or A* rating for A-level mathematics;

• a score of 4 or 5 on the AP Calculus AB or BC exam; or

• evidence of the successful completion of online courses with similar content.
   

Applicants are not expected to have published academic work previously, although publication may help the assessors judge your writing ability and thus could help your application.
 

In almost all cases, Social Data Science will require the use of statistical or programmatic approaches. The OII teaches primarily in the Python programming language. Students in our MSc programme will be taught in Python alongside other languages in specific circumstances where applicable. Applicants are not expected to have extensive programming skills in Python. It is strongly encouraged for applicants to have at least a working familiarity with the basics of programming, regardless of language.
 

Academic research related to data science or experience working in related businesses is not required, but may be an advantage.

Home  
 £25,760

Overseas  
 £30,910

Employers recognise the value of a degree from the University of Oxford, and graduates from our existing programmes have secured excellent positions in industry, government, NGOs, or have gone on to pursue doctoral studies at top universities.
 

For example, non-academic destinations of recent graduates have included large technology companies such as IBM, Google or Meta; smaller start-ups like Academia.edu, Spotify, TikTok, and Bumble; and positions with regulators or government agencies globally. MSc alumni have progressed to further graduate study at institutions such as Cambridge, Harvard, Columbia, Princeton, Sciences Po, and LSE.
 

The OII Alumni Wall features interviews from both MSc and DPhil alumni about their time at the Department and career paths after Oxford.