We are Entain. Our vision is to be the world leader in sports betting and gaming entertainment by creating the most exciting and trusted experience for our customers, revolutionising the gambling space as we go. We are home to a global family of more than 25 well-known brands, and with a focus on sustainability and growth, we will transform our sector for our players, for ourselves and for the good of entertainment.
To maintain our pace of delivery, we are looking to scale the data science and ML engineering team across several areas. Initially focusing on data engineering, data ops engineering, and machine learning (ML) engineering. These roles will be essential to the scale out, and operational stability of our model and platforms, both today and in the future.
We encourage you to join an energetic and vibrant team of data scientists and data engineers excited to utilise and advance a modern technology stack to make a real impact on the business. Bring your ideas, drive, team spirit and love of data and let us get started!
We are a distributed team central to Entain, building intelligent automated decisioning tools, across all our geographies and brands, to acquire, retain and engage our customers. This gives us a vast range of opportunities to work on and take ownership of, our work is paramount to the company’s vision and success. You can choose one of our offices based in London or Gibraltar.
We recognize that everyone brings an outstanding set of skills, so the role profiles mentioned below are intentionally generic – if your experience, skills, and appetite fit across one or more of these roles, we'd love to hear from you.
Data Engineer:
- Designs, builds, tests, optimizes, and supports data preparation components.
- Ensures timely release of these components to the production environment.
- Drives standard methodology for data engineering across the wider analytics teams, factoring in the specific design, architecture, and technology in place within Entain.
- Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
- Performs data analysis required to solve data related issues and assist support teams in the resolution of data issues.
Data Ops Engineer:
- Establish the processes and automation requirements to efficiently operate the data estate at scale.
- Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
- In collaboration with engineering and firmwide data, determine the required toolsets, patterns and standards which will enable further scale out of our machine learning and data science estate.
- Identify, design, and implement internal process improvements targeting scalability, optimizing data delivery, and automating manual processes.
ML Engineer:
- Acts as the bridge between application software engineering and data science. Will deliver code and associated artefacts to ensure we design and build solutions appropriate to the use case.
- Enable the scale up/out of PoC models to production grade assets.
- Collaborates with Architects to review and validate designs.
- Leverage existing tools and frameworks, suggesting opportunities to improve and extend where relevant.
- Interprets wider engineering trends and patterns, establishing opportunities for Entain. (Lead)
If you are interested in being part of something phenomenal and driving your career within Data Science and Data Engineering forward then we are keen to hear from you! Apply directly and get in touch with [email protected] for more information.
