ML/DataOps Manager
FDJ United is seeking a DataOps / MLOps Manager to lead the evolution of its machine learning platform and data operations capability. This role focuses on the Sportsbook product, aiming to enable faster, more reliable, and scalable delivery of data and machine learning products. The position is central to building and operating the foundations that support end-to-end machine learning workflows, spanning from research and experimentation to production deployment and monitoring.
The successful candidate will lead a team responsible for DataOps and MLOps practices, working in close alignment with Data Engineering, Machine Learning Engineering, Quants, and Data Science teams. As FDJ United scales its personalisation, customer risk, and trading optimisation capabilities, this role will be instrumental in shaping the tooling, standards, and processes that allow teams to iterate quickly while maintaining high levels of reliability, governance, and compliance.
- Lead and grow a team of DataOps and MLOps engineers, providing technical direction, coaching, and career development.
- Define and drive the strategy for DataOps and MLOps capabilities across the sportsbook data platform.
- Build and evolve the platform and tooling that supports end-to-end machine learning lifecycle management, including development, deployment, monitoring, and retraining.
- Establish best practices for data and machine learning workflows, including automated testing, deployment, and rollback strategies.
- Work with DevOps to evolve infrastructure as code practices (e.g. Terraform, CloudFormation) to ensure scalable and reproducible environments.
- Collaborate with Data Engineers, Quants, and ML Engineers to improve developer experience, platform usability, and delivery velocity.
- Implement robust monitoring, observability, and alerting across data pipelines and ML models (including model performance and drift).
- Drive standardisation of tooling and workflows across teams, balancing flexibility with consistency.
- Ensure data and model governance practices are embedded, including reproducibility, lineage, discoverability, and compliance.
- Partner with product and business stakeholders to align platform capabilities with strategic priorities.
- Manage platform reliability, performance, and cost efficiency within AWS.
- 5+ years of relevant commercial experience, including experience in DataOps, MLOps, or platform engineering roles (required)
- Proven experience leading or mentoring engineers in a technical environment (required)
- Strong understanding of data engineering and machine learning workflows and how they operate in production (required)
- Experience implementing CI/CD pipelines for data and/or machine learning systems (required)
- Experience with Infrastructure as Code (Terraform, CloudFormation, or similar) (required)
- Strong experience with cloud platforms, ideally AWS (required)
- Experience with distributed data processing technologies (e.g. Spark) and streaming platforms (e.g. Kafka) (required)
- Ability to operate at both a strategic and hands-on level when required (required)
- Strong communication and stakeholder management skills, with the ability to align cross-functional teams (required)
- Proactive mindset with the ability to navigate ambiguity and drive continuous improvement (required)
- Experience in sports betting, trading platforms, or regulated industries (nice-to-have)
- Familiarity with modern ML tooling (e.g. feature stores, model registries, experiment tracking platforms) (nice-to-have)
- Knowledge of data architecture patterns such as Data Mesh or medallion architecture (nice-to-have)
- Experience with observability and monitoring tools for data and ML systems (nice-to-have)
- Experience building internal platforms or developer tooling (nice-to-have)
- Passion for mentoring and building high-performing teams (nice-to-have)
- Learning and development opportunities
- Social events and activities
- Inclusion networks
- Employee Assistance Programme
- Private medical insurance
- Long service awards
- Pension
FDJ United is one of Europe's largest gaming and betting groups, formed after French lottery operator La Française des Jeux (FDJ) acquired Kindred Group - the company behind Unibet - in 2024 and rebranded the enlarged group in 2025. Headquartered in Boulogne-Billancourt, France, it operates lottery, online sports betting, casino and poker across multiple European markets and Australia. Its portfolio includes well-known online brands such as Unibet, 32Red and Maria Casino, alongside FDJ's French lottery and retail network. The group is listed on the Euronext Paris exchange.