Football Modelling Quant Analyst - Hybrid/Remote Europe

Moretus Advisors LLC; 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

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.