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Quantitative Analyst – Football

London, London, United Kingdom

Actively hiring, first seen by us 1 day ago
Pay
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Work setting
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Employment
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Education & alternatives
- MSc in Statistics or a related field (e.g., Data Science or Mathematics) with 3+ years of relevant work experience (e.g. sports quantitative analyst for a club, betting syndicate, or bookmaker. Or, - PhD or equivalent in Statistics or a related field (e.g. Data Science, Mathematics). Candidates from adjacent fields (Computer Science, Engineering, Finance) are welcome via either route, provided they have solid applied statistics experience.
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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 4, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 5, 2026

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  • Julia
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  • MongoDB
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  • PostgreSQL
Where the posting names them
- Experience with version control, code reviews and merge requests. - Experience with any additional programming languages (such as Python, C++ or Julia). - Familiarity with database technologies, e.g., SQL, MongoDB, Redis, Postgres.
- Model diagnostics: Ability to evaluate predictive model performance using appropriate metrics, quantify and communicate predictive uncertainty. - Strong programming skills in a high-level language such as R (preferred) or Python. Must write production-quality code not just analysis scripts. - Clear written communication and documentation (including mathematical), can implement formulas from specs and code from formulas.
- Experience with any additional programming languages (such as Python, C++ or Julia). - Familiarity with database technologies, e.g., SQL, MongoDB, Redis, Postgres. What you can expect in return – Our Benefits

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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 will be responsible for providing clients with predictions for football outcomes across 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 performance provide immediate feedback on model quality. This makes the job challenging but also very exciting.  

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

We highly value the personal development of our team members and you will therefore be able to allocate dedicated 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 the minimum requirements, we would be especially keen to hear from applicants with substantial research experience and a demonstrable passion for football analytics. 


Key Responsibilities
  • Contribute to identifying promising research directions; ensuring research is carried out to the highest standard. 

  • Extend existing predictive models for football and develop new ones, aligned with the needs of clients and the business. 

  • Own and execute the relevant research projects, providing updates and estimates for delivery. 

  • Contribute to discussions and efforts to identify weaknesses and potential improvements in existing models across all sports. 

  • Contribute to the review of the work and code of others within the team. 

  • Develop and maintain software 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 

Either :

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

  • PhD or equivalent in Statistics or a related field (e.g. 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 GAMs and GLMs. 

  • Model diagnostics: Ability to evaluate predictive model performance using appropriate metrics, quantify and communicate predictive uncertainty. 

  • Strong programming skills in a high-level language such as R (preferred) or Python. Must write production-quality code not just analysis scripts. 

  • Clear written communication and documentation (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 and properly tested code. 

  • Thorough and reliable, with a verification mindset. 

  • Ability to work autonomously while communicating pro-actively any blockers when needed. 

  • Self-directed researcher who generates hypotheses worth testing and sees connections across domains. 

Others
  • Ability to work in the UK

Preferred 

  • Demonstrated passion for working in sports modelling and sports analytics.: Evidenced by personal projects, MSc project in a related area, or statistical analyses of sports or teams. 

  • Comfortable in R, in particular with data.table, mgcv and testthat for unit testing. 

  • Engineering discipline: unit testing, config-driven pipelines, clean git workflow. Willing to write tests, document as 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 verifies behaviour before committing. 

  • Experience with and/or knowledge of Bayesian models, state space models, filtering and smoothing, computational statistics and approximate inference methods. 

  • Experience with and/or knowledge of machine and statistical learning, deep neural networks, feature engineering, reinforcement learning, dynamic optimisation and optimal control. 

  • Experience with version control, code reviews and merge requests. 

  • Experience with any additional programming languages (such as Python, C++ or Julia). 

  • 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
*Available on selected days

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
  • Increase in Employer Pension to 6% (to a minimum employee contribution of 3%)
  • Enhanced Maternity Pay
  • Enhanced Paternity Pay
After 4 Years
  • Increase in Employer’s Pension to 7% (to a minimum employee contribution of 3.5%)

If this sounds like the right fit, we would love to hear from you. Please submit your CV and a cover letter explaining your interest in football analytics and highlighting relevant technical experience 

 
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