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1 Year On Campus Masters Program
Imperial College LondonThe MSc in Statistics (Data Science) at Imperial College London is a rigorous and prestigious STEM-designatedprogram that offers advanced training in modern statistical methods, data science, and machine learning. Hosted by the internationally renowned Department of Mathematics, the program focuses on both the theoretical underpinningsand practical applications of data-driven analytics.
Situated in the heart of London and ranked among the world’s top universities, Imperial’s program is designed for mathematically strong students seeking to become high-impact professionals in academia, research, finance, technology, and beyond.
Program Format & Duration
Full-time, on-campus (London, UK)
Duration: 1 year (12 months)
Department: Mathematics
Start Date: October
Award: MSc Statistics (Data Science)
STEM-designated
Core Curriculum Components
The MSc Statistics (Data Science) curriculum is built around a strong foundation in statistical methodology, enriched by computational tools and data science applications.
Core Modules
Statistical Foundations
Statistical Inference
Applied Bayesian Methods
Generalised Linear Models
Multivariate Analysis
Computational and Data Science Tools
Programming in R and Python
Computational Statistics
Machine Learning
High-dimensional Statistical Modelling
Electives and Specialist Options (sample)
Deep Learning
Time Series Analysis
Network Data Analysis
Statistical Finance
Bioinformatics and Genomics
Causal Inference
Spatial Statistics
Research Project (Dissertation)
A significant independent research project conducted during the summer term
Students work under faculty supervision to explore a challenging problem in statistics or data science
Projects may be theoretical, applied, or conducted in collaboration with external partners or industry
Imperial integrates theoretical depth with real-world application, offering students substantial opportunities for applied learning.
Dissertation Project
Conducted over the summer term
May involve industry collaboration, original research, or methodological development
Culminates in a formal report and potential publication
Hands-On Practice
Programming-intensive coursework using R, Python, and other tools
Projects and assignments based on real datasets from finance, healthcare, policy, and tech
Emphasis on reproducible research and ethical data use
Industry Engagement
Close ties to financial services, technology firms, pharmaceuticals, and government agencies
Access to guest lectures, career panels, and networking events
London location provides rich internship and job placement opportunities
Graduates of the MSc in Statistics (Data Science) from Imperial College London are highly sought after in both academic and industry roles due to their rigorous training and analytical expertise.
Career Outcomes
Typical job titles include:
Data Scientist
Machine Learning Engineer
Quantitative Analyst
Research Statistician
Risk Modeller
Data Analyst (Healthcare/Finance/Tech)
Top Employers
Alumni have joined:
Google, DeepMind, Meta, Amazon
HSBC, JP Morgan, Barclays, Morgan Stanley
GSK, AstraZeneca, NHS
UK Government and policy research units
PhD programs and research institutions worldwide
Further Study
Graduates may pursue:
PhDs in Statistics, Machine Learning, AI, or Computational Biology
Research fellowships in healthcare, social science, and economics
Dual degrees or advanced certifications in finance, public policy, or engineering
Academic Degree: Hold a UK upper second-class honours degree (2:1) or equivalent in a quantitative discipline (e.g., statistics, mathematics, computing, engineering, physics) Quantitative & Programming Background: Demonstrate strong knowledge in mathematical methods, linear algebra, probability/statistics, and programming (Python, R, MATLAB, etc.).Transcripts & References: Provide a complete application including an academic transcript and two references via the online application system, with originals required only upon admissionPersonal Statement: Submit a written personal statement explaining your background, motivations for the course, and academic preparednessEnglish Proficiency: International students must meet minimum scores—IELTS ≥ 7.0, TOEFL ≥ 100, PTE ≥ 69, or Duolingo ≥ 125—or complete a suitable English program Application Fee: Pay an £80 fee when submitting your application online Entry Requirements Compliance: Fulfill degree classification, quantitative background, English proficiency, and references before the final deadline (typically early July for September entry) .Potential Interview: Shortlisted applicants—especially those with non-traditional backgrounds—may be invited for a brief interview (in-person or via video) .StatisticianData ScientistQuantitative AnalystRisk AnalystBiostatisticianMachine Learning SpecialistStatistical ConsultantData AnalystData Engineer
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