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Maths Graduate CV Example

A maths graduate CV presents your strong analytical and quantitative skills, problem-solving abilities, and logical thinking for careers in finance, data science, technology, or research.

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Key Skills to Include

Mathematical ModellingStatistical AnalysisPython/R/MATLABData AnalysisLogical ReasoningProblem SolvingLaTeXAlgorithm Design

Quick Tips

  • Highlight specific areas of mathematics you specialise in, such as statistics, applied maths, or pure maths.
  • Include programming skills and experience with mathematical software.
  • Mention any competitions, prizes, or scholarship awards that demonstrate your mathematical ability.
  • Tailor your CV to show how mathematical skills translate to your target industry.

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How to Write Your Maths Graduate CV

A maths graduate CV must demonstrate your analytical power, problem-solving skills, and ability to apply mathematical thinking to practical challenges. Mathematics graduates are highly sought after in finance, data science, technology, consulting, and research because of their rigorous training in logical reasoning and quantitative analysis. Your CV should showcase both your mathematical expertise and the practical skills you have developed through programming, projects, and any work experience.

CV Structure

Use a reverse-chronological format with a profile, work experience or projects, education, and skills sections. If you have limited professional experience, create a dedicated section for academic projects that demonstrate applied mathematical skills. Place your programming and software skills prominently, as these are often used as screening criteria. Keep the CV to one or two pages.

CV Format

Choose a clean, professional template. Avoid overly academic formats unless you are targeting research roles. Ensure your CV is easy to scan quickly, with clear headings and bullet points. If you mention specific mathematical methods, ensure the terminology is appropriate for your target audience — use plain language for non-technical employers.

CV Profile Examples

Data Science-Track Graduate

Mathematics graduate from Imperial College London with a first-class MMath degree and a strong specialisation in statistics and machine learning. Proficient in Python, R, and SQL with experience building predictive models and analysing large datasets through academic projects and a summer data science internship. Seeking a graduate data scientist or quantitative analyst role.

Finance-Track Graduate

Highly numerate mathematics graduate from the University of Warwick with a 2:1 degree and a keen interest in quantitative finance. Completed modules in stochastic processes, financial mathematics, and optimisation. Experienced in building pricing models using MATLAB and Python. Targeting a graduate role in risk management, trading, or quantitative analysis.

Applied Maths Graduate

Applied mathematics graduate from the University of Cambridge with a 2:1 degree and a final-year project modelling fluid dynamics in cardiovascular systems. Skilled in numerical methods, differential equations, and scientific computing using MATLAB and C++. Seeking a graduate position in engineering analysis, scientific computing, or operations research.

State your degree, university, classification, and area of mathematical specialisation. Mention your key technical skills, particularly programming languages and data analysis tools. Conclude with the type of role you are targeting and the value you intend to bring.

Key Skills for Your Maths Graduate CV

Mathematical Modelling

Constructing mathematical representations of real-world systems to analyse behaviour, predict outcomes, and optimise solutions.

Statistical Analysis

Applying statistical methods including regression, hypothesis testing, and Bayesian inference to analyse data and draw conclusions.

Python/R/MATLAB

Writing code for numerical computation, data analysis, statistical modelling, and visualisation in multiple programming environments.

Data Analysis

Processing, cleaning, and interpreting large datasets to extract meaningful insights and support decision-making.

Logical Reasoning

Applying formal logic and structured thinking to decompose complex problems and develop rigorous solutions.

Problem Solving

Approaching unfamiliar and challenging problems methodically, testing approaches, and refining solutions iteratively.

LaTeX

Typesetting mathematical documents, reports, and presentations using LaTeX for professional-quality output.

Algorithm Design

Designing efficient computational algorithms for sorting, searching, optimisation, and data processing tasks.

Mathematical Communication

Explaining complex mathematical concepts clearly to both technical and non-technical audiences in writing and presentations.

Work Experience Examples

Detail any internships, research projects, or teaching roles that demonstrate applied mathematical skills. Describe the problems you worked on, the methods you used, and the results you achieved. For data science or finance roles, mention specific modelling techniques and software tools. Quantify your impact wherever possible.

Data Science Intern

Experian plc, Nottingham

Completed a 10-week summer internship in the data analytics team, developing predictive models for consumer credit risk assessment.

Responsibilities

  • Cleaned and prepared large consumer credit datasets using Python and pandas, handling missing values and feature engineering.
  • Built logistic regression and random forest classification models to predict default probability on unsecured lending products.
  • Evaluated model performance using ROC curves, confusion matrices, and cross-validation techniques.
  • Presented interim and final results to the analytics team, explaining model methodology and key findings.
  • Documented code, methodology, and results in a technical report following the team's documentation standards.

Achievements

  • Developed a feature engineering approach that improved the default prediction model's AUC score from 0.78 to 0.83.
  • Received a return offer for a graduate data scientist position based on the quality and impact of the internship project.

Undergraduate Teaching Assistant

Imperial College London, Department of Mathematics

Supported first-year mathematics undergraduates with weekly problem classes in linear algebra and calculus, marking coursework and providing feedback.

Responsibilities

  • Led weekly problem classes for groups of 15 students, guiding them through worked examples and encouraging collaborative problem solving.
  • Marked and provided detailed written feedback on fortnightly problem sheets, identifying common errors and misconceptions.
  • Held weekly office hours for one-to-one support, helping students who were struggling with course material.
  • Attended training sessions on effective teaching practices and provided feedback to the module leader on student performance trends.

Achievements

  • Received an average student feedback rating of 4.8 out of 5 for clarity of explanations and approachability.
  • Identified a recurring misconception in matrix diagonalisation that was addressed in the following year's lecture notes.

Education & Qualifications

List your degree with classification and highlight relevant modules and your final-year project. Mention any academic prizes, scholarships, or competition achievements. Include programming skills acquired through your degree. Follow with A-levels, emphasising Mathematics and Further Mathematics grades.

MMath/BSc Mathematics

An undergraduate or integrated masters degree providing rigorous training in mathematical theory and problem-solving methods.

Programming Certifications

Formal certifications in Python, R, or other programming languages that complement mathematical skills.

A-Level Mathematics & Further Mathematics

Advanced-level qualifications demonstrating exceptional mathematical ability and preparation for degree-level study.

UKMT/Olympiad Achievements

Competitive mathematics achievements demonstrating exceptional talent and problem-solving ability.

Frequently Asked Questions

What careers are best suited to maths graduates?
Mathematics graduates are highly employable in data science, quantitative finance, actuarial science, software engineering, operations research, academic research, and consulting. Your mathematical training in logical reasoning, statistical analysis, and problem solving is valued across almost every industry. Tailor your CV to emphasise the skills most relevant to your target sector.
How important are programming skills for maths graduates?
Programming skills are essential for most graduate roles available to maths graduates. Python is the most versatile language to learn, followed by R for statistical work and MATLAB for scientific computing. SQL is also valuable for data-related roles. Employers want to see that you can implement your mathematical knowledge computationally, so list your programming skills and describe the contexts in which you have used them.
Should I include my final-year project on my maths CV?
Yes, your final-year project is one of the strongest demonstrations of your ability to work independently on a complex mathematical problem. Include the title, a plain-language summary of the problem and your approach, and the key results. If you used programming or developed original mathematical models, highlight these. This is particularly important for research, data science, and quantitative finance roles.
How do I make a maths CV accessible to non-technical recruiters?
Use clear, non-jargon descriptions of your mathematical skills and project work. Instead of listing theorems, describe the types of problems you can solve and the tools you use. Frame your skills in terms of business value, such as predicting trends, optimising processes, or managing risk. Save technical detail for interviews or supplementary materials, and keep your CV focused on impact and capability.

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