Soccer Data Analyst at New England Revolution
Job Description
New England Revolution are recruiting a Soccer Data Analyst to apply advanced analytics, statistical modelling and data science to support decision-making across performance, coaching, scouting and player recruitment.
The successful candidate will work with a range of soccer event, tracking, physical and performance data, developing models and analytical tools that turn complex datasets into actionable football insights.
This is a particularly interesting opportunity for an analyst looking to combine football knowledge with Python, statistical modelling, machine learning and data visualisation inside a professional MLS environment.
- Analyse event, tracking, physical and performance data to identify meaningful trends and insights.
- Support match preparation, opposition analysis, player development and post-match review.
- Design and develop diagnostic, predictive and prescriptive analytical models.
- Build tools to support player evaluation, scouting, recruitment and roster construction.
- Develop interactive dashboards, visualisations and analytical reports.
- Undertake research projects using event, tracking and performance datasets.
- Develop and maintain analytical code and data pipelines using Python, R and SQL.
- Manage, validate and cleanse data from multiple sources.
- Support data governance and data-quality processes.
- Present complex analytical findings clearly to both technical and non-technical football stakeholders.
- Contribute to wider analytical projects across the organisation.
- Bachelor’s degree in Statistics, Economics, Mathematics, Computer Science, Data Science or another quantitative discipline.
- 2–4 years’ professional experience in analytics, data science, sports analytics or a related field. Relevant graduate research experience may also be considered.
- Knowledge of statistical analysis, predictive modelling and machine-learning methodologies.
- Advanced proficiency in Python and Excel.
- Experience integrating and managing multiple data sources and large datasets.
- Strong analytical, problem-solving and data-visualisation skills.
- Ability to communicate analytical findings effectively to different audiences.
- Master’s degree in Data Science, Statistics, Computer Science, Analytics or related discipline.
- SQL and relational databases.
- R, Tableau, Power BI and Git/version control.
- Experience working with football datasets from platforms such as Opta, StatsBomb, SkillCorner, Tracab or Catapult.
- Knowledge of football and an interest in applying analytics to performance, tactics and recruitment.
This is a strong opportunity for an early-career football data analyst looking to work across multiple areas of the game rather than within a narrowly defined analytics function.
The breadth is particularly attractive: performance analysis + tracking data + modelling + recruitment + scouting + research + decision-support tools.
Candidates should be prepared to work evenings and weekends and travel when required by the football schedule.