MSc Scientific Computing and Data Analysis (Financial Technology)

1 Years On Campus Masters Program

Durham University

Program Overview

The MSc in Scientific Computing and Data Analysis (Financial Technology) at Durham University combines advanced computing, mathematical modelling and data-analysis training with specialised study of financial systems and fintech applications. It suits quantitatively strong students—typically from maths, physics, engineering or computer science—who want careers in quantitative finance, fintech, risk modelling or computational analysis.

Curriculum Structure (Full-time, 1 Year)

Year of Study

Students begin with core modules such as Introduction to Machine Learning and Statistics, Introduction to Scientific and High Performance Computing, and Professional Skills, developing foundations in statistical modelling, numerical computation, scientific programming and research methods. They then specialise in Financial Technology, learning how computational and statistical techniques are applied to financial markets, pricing models, risk assessment and large-scale financial data analysis. The programme concludes with a major Project, where students integrate computing, mathematics and financial modelling to address a real or research-oriented fintech or quantitative-finance problem.

Focus areas: “Scientific computing, machine learning, high-performance computing, financial modelling, quantitative finance, fintech data analysis”

Learning outcomes: “Apply ML and statistical tools; perform high-performance numerical computation; model financial systems and pricing; analyse financial risk and big-data markets; complete an applied or research-based fintech project.”

Professional alignment (accreditation): Master’s-level training aligned with industry and research needs in fintech, quantitative finance and computational modelling.

Reputation (employability rankings): Durham is consistently ranked among top UK universities, with strong outcomes in quantitative and computational fields; graduates progress into fintech firms, quantitative-finance roles, data-driven financial analysis, and doctoral research.

Experiential Learning (Research, Projects, Internships etc.)

The MSc Scientific Computing and Data Analysis (Financial Technology) at Durham University applies advanced computational and data science techniques to financial markets and FinTech. Students gain practical skills in quantitative analysis, algorithmic modelling, and financial data processing using high-performance computing.

Key experiential components:

Software & Tools: Financial data analysis using Python (Pandas, NumPy, scikit-learn), R, and FinTech-specific libraries for algorithmic trading, risk modelling, and blockchain applications.
Computing Facilities: Access to Durham's High-Performance Computing (HPC) resources and the Data Intensive Science Centre for running complex financial simulations and back-testing trading strategies.
Group Projects: A core collaborative quantitative project, where student teams analyse financial datasets, develop predictive models, or design algorithmic trading prototypes.
Research & Industry Context: Curriculum is informed by Durham's Department of Mathematical Sciences and Durham University Business School, with dissertation projects often tackling current problems in quantitative finance or FinTech innovation.

Progression & Future Opportunities

Graduates of Durham University's Scientific Computing and Data Analysis (Financial Technology) MSc secure roles as financial software engineers, quantitative analysts, fintech developers, and data scientists in banking, hedge funds, insurance, and tech firms:

Durham’s Careers Service delivers coaching, CV workshops, employer events, and alumni networks for placements.
Excellent employability with alumni at Google, investment banks; competitive fintech salaries (£40,000+ starting UK).
Partnerships with Jaguar Land Rover, GCHQ, Boeing, and Procter & Gamble enable industry projects and dissertations.
Research-led qualification supports Chartered IT Professional status and fintech career longevity.
Outcomes span software development, finance consulting, startups, or PhDs.

Further Academic Progression: Graduates can advance to PhDs in computer science, fintech, or data analysis at Durham, leveraging MSc projects in financial modeling and computing for research careers.

Additional Information & Requirements

All streams require a 2:1 BSc (Honours) degree or international equivalent.

India- A 3, 4 or 5-year Bachelor's degree from an approved Indian university with a score of 55%-65% depending on the institution.

USA- A Bachelors degree from an accredited university with a GPA of 3.3 or better out of 4.0.

IELTS- 6.5 with no component under 6.0

TOEFL: 80 with no component under 20

China- A standard full-time bachelor’s degree (4 years minimum), with a minimum average grade of between 75% - 85% from a recognised prestigious university.

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