At a Glance
- Tasks: Analyse football data and develop predictive models for betting markets.
- Company: Join Smartodds, a dynamic team in North London focused on sports analytics.
- Benefits: Enjoy 30 days holiday, in-house chef, and professional development opportunities.
- Other info: Experience exciting career growth and attend industry events to enhance your skills.
- Why this job: Combine your passion for football with cutting-edge statistical modelling in a collaborative environment.
- Qualifications: MSc or PhD in Statistics or related field, with strong programming skills.
The predicted salary is between 47250 - 57750 £ per year.
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
Either
- 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,
- Ph D 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 GAMsand GLMs.
- 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++or Julia).
- Familiarity with database technologies, e. g., SQL, Mongo DB, 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%)
- #J-18808-Ljbffr
Quantitative Analyst – Football employer: Smartodds
Smartodds is an exceptional employer that fosters a collaborative and innovative work culture in the heart of North London. With a strong emphasis on employee growth, we offer continuous learning opportunities, peer reviews, and the chance to engage in impactful projects that shape the future of automated betting strategies. Join us to be part of a dynamic team where your contributions are valued and rewarded.
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We think you need these skills to ace Quantitative Analyst – Football
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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