Data Scientist

About Us

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?

• Introduction:

  We are building the sportsbook of tomorrow at Kindred. Machine learning algorithms and AI are at the heart of how we will deliver an unrivalled customer experience and unlock operational efficiencies through automation.

  Our Data Science (DS) and Machine Learning Engineering (MLE) teams are currently focused on delivering Personalisation and Risk Management products, with future scope to develop sportsbook specific Reward products, and collaborate with our Quant team to develop trading automation solutions.

  We are recruiting a Data Scientist to join our product-led team and contribute to the success of our Kindred Sportsbook Platform. This role will report into our Risk Management team.

  Key responsibilities:

  • Actively contribute to product development, able to interpret requirements and deliver independently.
  • Collaborate with DS and MLE team members to build and deliver data-driven products.
  • Take technical ownership of models throughout their lifecycle.
  • Write code that follows best practices and facilitates collaboration and re-usability.
  • Work closely with business stakeholders to translate business requirements into data science use cases, proactively reaching out in ambiguous situations, adapting to feedback and generating insights/solutions backed by data to drive the decisions.

  To be successful in this role, we think you will hit many of the below criteria:

  • Bachelor's or advanced degree in a STEM subject.
  • Experience in a DS role with a proven track record successfully delivering algorithmic data products for enterprise-grade solutions in collaboration with engineering teams.
  • Proactively solving problems and proposing new solutions where existing methodology may not exist.
  • Accountability for the decisions taken within the projects and ability to clearly explain the reasoning
  • Interest and understanding of sports betting, experience in sports risk management.
  • Excellent interpersonal skills, able to explain complex concepts to stakeholders.
  • Strong knowledge of machine learning algorithms and general statistical methodologies and theory.
  • Basic knowledge of AB testing and design of experiment.
  • Advanced Python and SQL skills, experience using Spark for processing large datasets.
  • Understanding of software product development processes and governance, including CI/CD processes and release and change management.
  • Familiarity with cloud computing platforms, ideally experience with Amazon Web Services.

Our Way Of Working

Our world is hybrid.

A career is not a sprint. It’s a marathon. One of the perks of joining us is that we value you as a person first. Our hybrid world allows you to focus on your goals and responsibilities and lets you self-organise to improve your deliveries and get the work done in your own way.

Application Process

We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.