AFC Bournemouth is a forward thinking and ambitious club who are seeking to recruit a data scientist to enhance and support the day-to-day processes of the analytics department. The successful candidate will be based at the club’s training ground, working with the first team match analysis and recruitment departments.
The data scientist will report to the Head of Analysis & Recruitment Coordinator, working closely with first team staff from both departments.
- Work in line with the club’s philosophy on data analysis & modelling, to contribute to its future progression
- Create, maintain and progress data analytics tools that enhance decision making processes
- Manage large volumes of data, including merging information from various sources
- Automate manual processes to increase efficiency in both departments
- Adapt to the requests/needs of various staff within the team as a collective
- A portfolio of work, demonstrating an ability to work with large datasets, to build, maintain and display output that enhances subjective analysis of team performance and/or player recruitment
- Extensive experience of programming language (Python/R)
- Experience working with raw data, including event & tracking data (e.g. Opta f24)
- Understanding and experience with web technologies
- Creative and effective data visualisation skills (e.g. experience with Tableau)
- A sound understanding of the game. Including, but not limited to, the technical and tactical analysis of teams and individuals.
- Effective communication skills to present findings to staff members across different departments
- A strong work ethic, with an emphasis on flexibility in the working environment (to work alone or as part of a group).
- Minimum Bachelor’s level qualification in computer science/statistics (or similar)
To apply for this role, please send the following to email@example.com by 1st February 2020.
- Cover letter (explaining why you are suitable for the role)
- Curriculum vitae (including references)
- Examples of your work
- Your salary expectations