About the role

As a member of the Quant Team, you will join an exciting environment, predicting outcomes of professional sports on behalf of our clients. We focus on football, baseball, basketball, cricket, tennis, American football, ice hockey and horse racing. In this role, you will be the main Quant working on Tennis and will be responsible for developing statistical models for both pre-match and in-play. You will also support research into other sports, as well as investigate how our predictions can be leveraged to improve profitability and the overall commercial performance. Furthermore, you will play a key role in developing and supporting the reliable production of high-quality predictions for our clients. You'll have plenty of autonomy to execute your models from idea to code to validation to (hopefully) deployment, integrating your well-documented and tested code into our internal libraries. 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. The atmosphere is a collaborative academic one with peer reviews, research talks, and the opportunity for further education. Unlike academia though, the market is there to give immediate feedback on how good your model is. This makes the job challenging but also very exciting. While we are open to applications from anyone who meets the minimum requirements, we would be especially keen to hear from applicants with more substantial research experience for this particular role.

Key Responsibilities

• Contribute to identifying promising research directions; ensure research is carried out to the highest standard
• Develop tennis predictive models for both pre-match and in-play
• Contribute to discussions and efforts to identify weaknesses and potential improvements in existing models across all sports
• Support [Employer hidden]’ clients in their pricing tasks by developing, maintaining and supporting the mathematical libraries behind our range of tools and models and software that delivers model predictions into production
• Perform statistical analysis of datasets, testing well-defined hypotheses and effectively communicating results to the various stakeholders, including [Employer hidden]’ clients
• Attend at least one event to support your professional development as a sports quant analyst on an annual basis: conferences, courses, meet-ups, networking events; in-person or remotely; on sports, statistics, machine learning, gambling, etc.

Skills & Experiences

Required

• Either a MSc in Statistics or a related field (e.g., Data Science or Mathematics), or another field (such as Computer Science, Engineering, Finance, etc) with some experience in statistics and 3+ years of work experience in a relevant role, e.g Sports quantitative analyst for a betting syndicate or a bookmaker; or a PhD or equivalent in Statistics or a related field (e.g., Data Science or Mathematics), or another field (such as Computer Science, Engineering, Finance, etc) with some experience in statistics
• Extensive experience of probabilistic and statistical modelling
• Strong programming skills in a high-level language such as R or Python
• Demonstrated passion for working in sports modelling, evidenced by personal projects, MSc project in a related area or statistical analyses of sports or teams
• 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 proactively about any blockers when needed
• Good organisation and communication skills, including the ability to coordinate work across teams (data analysts, data engineers, software developers)
• Ability to communicate results to those with and without specialist knowledge
• Ability to work in the UK

Preferred

• A strong interest in tennis demonstrated by previous attempts to model outcomes or analyse data
• Good understanding of sports betting markets
• 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 automated trading systems
• Strong software development foundations
• Experience with any additional programming languages (such as C++ or Julia)
• Familiarity with database technologies, e.g., SQL, MongoDB, Redis, Postgres
• Experience with version control, code reviews and merge requests

Benefits

• From Day One: 30 days holiday, in-house chef*, in-house masseuse*, team sporting events, 25% 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%, employee starting at 2.5%; Income protection – 75% of salary (subject to terms & conditions)
• After Probation: 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 contribution to 6% (with a minimum employee contribution of 3%); Enhanced Maternity Pay; Enhanced Paternity Pay
• After 4 Years: Increase in employer pension contribution to 7% (with a minimum employee contribution of 3.5%)

About [Employer hidden]

[Employer hidden] is a privately-owned company providing statistical research and sports modelling services to customers, including professional gamblers and professional football teams. Our employees are based in North London with a number of consultants based globally. Founded in 2004, [Employer hidden] has a proven record of providing exceptional services to its clients. We are a growing company and work in an exciting and fast-paced industry of which we are a market leader. [Employer hidden]’ achievements are built around the talents of its employees. We like to think that despite the diverse background of the people who work at [Employer hidden], there is one thing we have in common: commitment and job satisfaction. As part of a fantastic team, [Employer hidden]’ employees enjoy the opportunity to be the very best at what they do, contributing to the success of the company on a daily basis.