The Role

The Quant Team specializes in developing and deploying advanced quantitative sports models, transforming them from prototype to production. As a key part of our evolving Sportsbook Platform, the team is divided into two areas: Quant Research and Quant Engineering, each playing a vital role in shaping the future of our sports modeling capabilities.

We are seeking a skilled Quant Model Engineer to enhance our internal Quant libraries, streamline model deployment, and optimize existing tools for peak performance.

Responsibilities

• Contribute to product development, delivering independently once requirements are clearly set
•  Support product delivery by collaborating with relevant stakeholders
• Plan and build Quant libraries and model fitting jobs in close cooperation with colleagues in the Quant Team and Pricing Engineering Team
•  Refine and optimise existing functionality, models, and tooling
•  Assist in developing and building APIs and interfaces to enable controlled access to Quant Team models and products
•  Support product maintenance and monitoring initiatives
• Write code following best practices, ensuring collaboration and reusability among team members
• Promote work and contributions within the team and across the broader business
• Help build scalable tools and applications to facilitate model evaluation
• Contribute to the deployment of developed software applications using CI/CD, containerisation, and DevOps best practices
• Ensure that you adhere to the Governance, Risk & Compliance (GRC) obligations for your role.
• Identify and raise any non-compliance incidents promptly to your line manager.
• Challenge processes, policies and projects that will negatively impact compliance within the Group.
• Complete all mandatory compliance training assigned to you.
• Reach out to the Compliance Teams if unsure of any of your compliance obligations or the requirements are unclear.

Expected Attributes

• Commercial experience in a similar role
• Strong knowledge of statistical and machine learning algorithms
• Experience building and deploying statistical or machine learning models in a production environment
• Demonstrable specialisation in building robust production-quality APIs and/or platform and tooling optimisation
• Intermediate programming skills in Python and SQL
• Experience interacting with databases
•  Experience deploying software into containerised environments
•  Problem-solving mindset with the ability to learn and adapt quickly.
• Constructive and collaborative approach when working with colleagues and broader stakeholders
• Proactive learner with a desire to expand technical skillset and grow professionally
• Well-organised, able to prioritise effectively, and comfortable with uncertainty
• Strong communication skills, able to convey technical topics to non-technical stakeholders

Desirable Attributes

• Master's or PhD in a STEM subject
•  Understanding of functional and object-oriented programming paradigms
•  Extensive experience interacting with relational databases
•  Practical MLOps experience
• Experience deploying containerised applications onto Kubernetes
•  Experience writing and deploying software within cloud-based environments, ideally AWS
•  Familiarity with component orchestration frameworks like Airflow or equivalent
• Experience working with sporting data or demonstrable knowledge and interest in this area, including sports betting
• Experience designing and building frameworks for model evaluation and/or back-testing

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