Senior Quant Model Engineer

About the Company

At FDJ UNITED, we don't just follow the game, we reinvent it. FDJ UNITED is one of Europe's leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you'll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day. We're looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field. Join us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?

About the Role

The Quant Team at FDJ develops and deploys quantitative sports models, enabling in-house pricing across a variety of sports, markets and products. The team is an important component of the vision for the future evolution of the FDJ United Sportsbook Platform. The Quant Team is split into two workstreams: Quant Research and Quant Engineering. We are looking for a talented Senior Quant Model Engineer to help us build and optimize predictive sports models as part of the Engineering team. The successful candidate will work very closely with the Quant Research team, as well as with architects, MLOps engineers and other key stakeholders. This position would be ideal for any strong software engineer or software-focused research analyst with strong proficiency in Python, an interest in sports betting, and the ambition to work on high-impact projects amongst a friendly and intelligent team!

Responsibilities

• Turn exploratory predictive models from the Research team into resilient and scalable model libraries and services.
• Be a key stakeholder in planning, designing, and implementing high-quality production code that will have a clear impact on the progression of products within the sportsbook.
• Build robust APIs and interfaces to allow controlled access to Quant's predictive models and data products.
• Make active contributions to the development of probabilistic pricing models and their efficiency.
• Work alongside senior Quant Team members to plan out and take ownership of long-term workstreams.
• Promote work and contributions for use within the team and the wider business, through global collaboration, conversations, written reports, and presentations.
• Dedicate time for investigating new techniques and methodologies that can benefit the team and wider business.

Qualifications

• A minimum of 4-5 years commercial experience in a similar role focussed on model development and deployment, as part of a quantitative or data science lifecycle.

Required Skills

• Excellent Python skills and advanced theoretical and applied understanding of the principles of object-oriented programming.
• Experience with Python libraries for optimised scientific computing, specifically NumPy, SciPy and Numba.
• Experience building and deploying statistical models in a production environment.
• Applied experience demonstrating specialism in building production quality APIs.
• Experience applying software development best practices such as version control, unit testing, linting and CI/CD.
• An excellent communicator, both written and verbal, able to explain complex topics to non-specialists.
• A problem-solving growth mindset with the ability to pick up new tools and concepts quickly.
• Confidence to make clear recommendations to support decision making, e.g. around project priorities and planning.

Preferred Skills

• Masters degree or PhD in STEM subject.
• Experience deploying containerised applications using Docker and Kubernetes.
• Experience writing and deploying software within cloud-based environments, ideally AWS.
• Experience with frameworks and technologies used in component orchestration, including Airflow or equivalent.
• Experience working with sporting data or demonstrable knowledge and interest in this area, including an interest in sports betting.
• Good knowledge of additional coding languages, for example Java or C++.