Quantitative Analyst – Football

Smartodds

City Of London

On-site

GBP 65,000 - 90,000

Full time

7 days ago

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Benefits offered by this job

30 days holiday

In-house chef

In-house masseuse

Brentford FC 20% discount

Cycle to work scheme

Employee Assistance Programme

Private Medical Insurance

Job summary

Smartodds is hiring a Quantitative Analyst - Football in North London. You will build and deploy predictive models for football outcomes, combining rigorous statistics with production-grade code in a collaborative setting.

The role emphasizes reproducible research, high test coverage, and ongoing professional development within a supportive, open culture. Applicants with strong research experience in football analytics are invited to apply.

Qualifications

MSc in Statistics or a related field with 3+ years of practical work experience.
PhD or equivalent in Statistics or related field is desirable.
Candidates from adjacent fields with solid applied statistics experience welcome.

Responsibilities

Extend predictive models for football and develop new ones for clients.
Own and deliver research projects with regular updates.
Review work and code within the team to ensure quality.
Develop and maintain software supporting model predictions and libraries.
Participate in research talks, reviews, and knowledge sharing.
Attend at least one event per year for professional development.

Skills

Statistical modelling

Model diagnostics

R or Python programming

Written communication

Autonomous work

Bayesian methods

Education

MSc in Statistics

PhD in Statistics

Tools

Python

SQL

Git

Job description

We have a fantastic new opportunity to join our team at Smartodds as a Quantitative Analyst - Football. Based in North London, Smartodds provides in-depth research and analysis on sporting events around the world, supported by world-class, bespoke software platforms. We are proud of our collaborative and dynamic culture, grounded in our core values of Boldness, Open-mindedness, Ownership, and Togetherness. We are a supportive and collaborative team - our environment is open, inclusive, and focused on doing great work together.

About the role

As a Quant Analyst, you willbe responsible forproviding clients with predictions forfootball outcomesacross various betting markets. This role combines rigorous statistical modelling with production engineering. You will take models from research through to deployment, writing well-tested, documented code that integrates into our internal libraries. The atmosphere is collaborative and academic-peer reviews, research talks, and further education opportunities-but unlike academia, the market performanceprovideimmediate feedback on model quality. This makes the job challenging but alsovery exciting.

You will have plenty of autonomy to execute your models from idea to code to validation to (hopefully) deployment. However, this autonomyoperateswithin a structured framework: established coding patterns, weekly check-ins, high test coverage, and strict reproducibility standards.

We highly value the personal development of our teammembersand you will therefore be abletoallocatededicated time to improve your skills and gain the necessary experience that will enable you to progress into more senior roles.

While we are open to applications from anyone who meets theminimumrequirements, we would be especially keen to hear from applicants with substantial research experience and a demonstrable passion for football analytics.

Key Responsibilities

Contribute toidentifyingpromising research directions; ensuring research is carried out to the highest standard.
Extend existingpredictive modelsfor football and develop new ones, aligned with the needs of clients and the business.
Ownand execute the relevant research projects, providing updates and estimates for delivery.
Contribute todiscussions and efforts toidentifyweaknesses andpotential improvements in existing models across all sports.
Contribute to the review of the work and code of others within the team.
Developandmaintainsoftware that supports the delivery of our model predictions, and the mathematical libraries behind our range of tools, providing updates and estimates for delivery.
Attend at least one event a year to support your professional development as a sports quant analyst: conferences, courses, meet-ups, networking events; in-person or remotely; on sports, statistics, machine learning, gambling, etc.

Skills & Experience

Required

Technical

MSc in Statisticsor a related field (e.g., Data Science or Mathematics)with 3+ years of relevant work experience (e.sportsquantitative analyst for a club, betting syndicate, or bookmaker. Or,
PhD or equivalent in Statistics or a related field (e.Data Science, Mathematics).

Candidates from adjacent fields (Computer Science, Engineering, Finance) are welcome via either route, provided they have solid applied statistics experience.

Applied statistics:Solid understanding of GAMsandGLMs.
Modeldiagnostics:Ability to evaluatepredictive model performance usingappropriate metrics,quantifyand communicate predictive uncertainty.
Strong programming skillsin a high-level language such as R (preferred) or Python. Must write production-qualitycodenot just analysis scripts.
Clear writtencommunicationanddocumentation(including mathematical), can implement formulas from specs and code from formulas.

Working style

Collaborative team player,with a constructive approach to receiving and applying feedback.
Understands the importance of reproducible research andproperly testedcode.
Thorough and reliable, with a verification mindset.
Ability to work autonomously while communicatingpro-activelyany blockers when needed.
Self-directed researcher who generates hypotheses worth testing and sees connections acrossdomains.

Others

Ability to work in the UK

Preferred

Demonstrated passion for working in sports modelling and sportsanalytics.:Evidencedby personal projects, MScprojectin a related area, or statistical analyses of sports or teams.
Comfortablein R,in particularwithdata.table,mgcvandtestthatfor unit testing.
Engineering discipline: unit testing, config-driven pipelines, clean git workflow. Willing to write tests,documentas you go, and follow strict code style.
Uses AI coding assistants as a development accelerator, not as a replacement for understanding. Writes precise instructions, reviews AI-generated diffs critically, and verifiesbehaviourbefore committing.
Experience with and/or knowledge of Bayesian models, state space models, filtering and smoothing, computationalstatisticsand approximate inference methods.
Experience with and/or knowledge of machine and statistical learning, deep neural networks, feature engineering, reinforcement learning, dynamicoptimisationandoptimalcontrol.
Experience with version control, codereviewsand merge requests.
Experience with anyadditionalprogramming languages (such as Python,C++orJulia).
Familiarity with database technologies, e.g., SQL, MongoDB, Redis, Postgres.

What you can expect in return – Our Benefits

From Day One

30 days holiday (in addition to bank & public holidays)
In-house chef*
In-house masseuse*
Team sporting events
20% discount on Brentford Football Club merchandise
Cycle to work scheme
Employee Assistance Programme
Interest-free travel season ticket loan
Offsite trips

After 3 Months

Pension - Employer Contribution starting at 5.5%, and employee starting at 2.5%
Income protection – 75% of salary (subject to terms & conditions)

After Probation

Dedicated time for professional development - conferences, courses, meet-ups, networking events (at least one annually)
Private Medical Insurance - including coverage of any excess payment
Health Cash Plan via Medicash
Life Assurance (4 x times earnings at time of death)
Enhanced Company Sick Pay
A discretionary annual bonus

After 2 Years