Quantitative Analyst – Football Modelling

Moretus; Greater London; Hybrid; GBP 120,000 - 160,000; Full time

Benefits offered by this job

Base salary £120,000–£160,000

Performance-based bonus

Hybrid work: 3 days in London, remote‑

25 days’ holiday + bank holidays

Workplace pension

Conference and training budget

Small team with direct impact

Job summary

Moretus in London is seeking a Quantitative Analyst focused on football modelling. You will build and refine statistical models for football markets, craft team and player strength metrics, and rigorously test models against market data.

The role blends research with production deployment in a hybrid London setting. You should have 3+ years in statistical modelling, strong statistics knowledge, and fluency in Python or R with SQL.

Qualifications

• 3+ years’ experience in statistical or predictive modelling.
• Strong statistics: probabilistic modelling, GLMs, Bayesian and hierarchical methods.
• Fluent Python or R, plus SQL.
• Understanding of betting markets as a benchmark and edge vs noise.
• Rigour about data leakage, overfitting and small samples.

Responsibilities

• Build and improve models for football markets, including match odds, Asian handicap and goal totals.
• Develop team and player strength ratings that respond to lineups, injuries and form.
• Evaluate models using calibration, log-loss and performance vs closing market prices.
• Work with league analysts to turn team news into model inputs.
• Run models in production on our data infrastructure.

Skills

Statistical modelling

Advanced statistics

Python or R

SQL

Football interest

Education

MSc in statistics/mathematics/physics/econometrics or equivalent

PhD in statistics or related field (or equivalent demonstrated work)

Tools

Python

R

SQL

Job description

Quantitative Analyst – Football Modelling Jobs in London Area, United Kingdom at Moretus

Title: Quantitative Analyst – Football Modelling

Company: Moretus

Location: London Area, United Kingdom

Quantitative Analyst – Football Modelling

Moretus | London (Hybrid) | Full-time

£120,000 – £160,000 + performance bonus

About Moretus

Moretus is a London-based sports betting and trading firm specialising in football. We build our own statistical models and price markets across leagues worldwide. We’re a small team growing our modelling function, and we’re looking for a quantitative analyst who wants to own models end to end and see their work tested against the market every week.

What you’ll do

• Build and improve models for football markets, including match odds, Asian handicap and goal totals
• Develop team and player strength ratings that respond to lineups, injuries and form
• Evaluate models rigorously using calibration, log-loss and performance against closing market prices
• Work with our league analysts to turn team news and match observation into model inputs
• Run your models in production on our existing data infrastructure

What we’re looking for

• 3+ years’ experience in statistical or predictive modelling
• Strong statistics: probabilistic modelling, GLMs, Bayesian and hierarchical methods
• Fluent Python or R, plus SQL
• An understanding of why the betting market is a tough benchmark, and how to tell real edge from noise
• Rigour about data leakage, overfitting and small samples
• A genuine interest in football
• MSc or PhD in statistics, mathematics, physics, econometrics or a similar field, or equivalent demonstrated work

Nice to have

• Experience in sports betting, trading or bookmaker pricing
• Experience with football event or tracking data
• Public work such as papers, GitHub projects, a blog or published models

What we offer

• £120,000 – £160,000 base salary depending on experience
• Performance-related bonus
• Hybrid working: 3 days a week in our London office. Fully remote within Europe considered for exceptional candidates
• 25 days’ holiday plus bank holidays
• Workplace pension
• Budget for conferences and training
• A small team where your work has direct impact and is judged by results

Moretus is an equal opportunity employer.