Your Role
We’re looking for a Lead Data Scientist to join our Global Football Metrics data science team, which is focused on delivering innovative machine learning models to keep Hudl at the cutting edge of sports analytics.
As a Lead Data Scientist, your key responsibilities will include:
- Work with a cross-functional team. You’ll collaborate with Engineering, Quality Assurance, Product, Design and Scrum disciplines to deliver cutting-edge tactical and recruitment insights.
- Develop and deliver. You will have access to industry-leading data from a variety of sources, and will lead the research and development roadmap for new Global Football models and metrics.
- Test new ideas. At Hudl, we iterate rapidly, deploying changes to the product hundreds of times daily across our Engineering team. In addition to working on concrete metrics, you’ll contribute to the implementation of scalable data pipelines and associated orchestration and monitoring tools.
- Mentor. You’ll share your expertise and educate others on development best practices and trade-offs, setting an example in planning, designing and delivering complex projects, and maintaining high standards of statistical rigour.
We’d like to hire someone for this role who lives near our office in London, but we’re also open to remote candidates. Remote candidates would have the ability to work from a co-working space or their home.
Must-Haves
- Technical expertise. You have a strong background in a quantitative discipline, and proven experience implementing statistical and machine learning models for statistical inference in complex systems.
- A team player. You understand that problem-solving is a team effort and will help others on our Engineering team learn and develop their skills.
- User-focused. You’re excited to have your work used by real people to solve real problems.
- Willing to learn. You have solid engineering skills but are always willing to dive into specific areas to gain the expertise needed to be successful in your role.
Nice-to-Haves
- Sports industry experience. If you’ve worked with event or tracking data previously, that’s a plus.
- Tech stack knowledge. Our tech stack is Python, PostgreSQL and Redshift. We will consider strong candidates with experience of R or Stan, but prefer those with more full stack skills and capable of writing production code.