University of York

What you'll study

The programme combines core analytical techniques, practical computing skills and business-facing modules to prepare you for applied analytics work. Teaching typically covers statistical modelling, predictive analytics and machine learning methods, optimisation and prescriptive analytics, data visualisation and storytelling, and database and big-data technologies.

• Quantitative Methods and Statistics – probability, inference, regression and time-series methods for business applications.
• Programming for Analytics – practical training in languages and environments commonly used in industry (for example Python or R), including data preparation and reproducible workflows.
• Machine Learning & Predictive Modelling – supervised and unsupervised techniques, model validation and deployment considerations.
• Optimisation and Simulation – prescriptive techniques for resource allocation, scheduling and supply-chain problems.
• Data Management and Big Data – relational databases, SQL and an introduction to scalable data-processing platforms.
• Data Visualisation & Communicating Insight – principles and tools for turning analysis into usable business recommendations.
• Professional Practice / Consultancy Project – group or individual project working on an applied analytics brief; many students undertake an industry-linked project or a dissertation driven by real data.

Modules are delivered through lectures, hands-on labs, case studies and group work. The programme culminates in a substantial project or dissertation that demonstrates your ability to apply methods to a real organisational problem.

Entry requirements

Applicants are normally expected to hold a good undergraduate degree (typically a UK upper second-class honours degree, or international equivalent) in a quantitative or numerate discipline such as economics, mathematics, statistics, computer science, engineering or a business subject with strong quantitative content. Candidates with degrees in other subjects but with relevant work experience, demonstrated mathematical ability, or prior programming skills may also be considered.

Applicants whose first language is not English will need to demonstrate proficiency to the University’s postgraduate standard. Shortlisted applicants may be asked to provide a CV, academic transcripts and references; some applicants could be invited to an interview or to complete an assessment task to demonstrate readiness for the technical content of the course.

Career prospects

Graduates go on to roles that apply data and analytics to business problems. Typical job titles include data analyst, business analyst, data scientist, analytics consultant, insight manager, operations analyst and quantitative modeller. Alumni work across sectors such as management consulting, finance, retail and e‑commerce, healthcare and pharmaceuticals, public sector and logistics, as well as technology start-ups.

The programme emphasises transferable skills sought by employers: technical competence with analytics tools, the ability to translate analysis into clear business recommendations, teamwork and project management. Many students leverage the dissertation or consultancy project to secure internships or graduate roles with partner organisations.

Why study at University of York

The University of York offers an interdisciplinary environment that brings together management, economics, computing and statistics expertise, enabling a curriculum that is both theoretically grounded and practically oriented. Teaching is informed by research and by collaborations with industry, giving students access to applied case studies and professional networks.

Students benefit from practical computing facilities, career and employability support tailored to data and analytics roles, and opportunities to engage in consultancy-style projects. York’s campus environment and supportive postgraduate community provide a focused setting for study, while links with regional and national employers help graduates transition into analytics careers.