Job information Division/Unit: Football Division/Club Competitions Contract type: Permanent Start date: 01.04.25 or as soon as possible Application deadline: 27.02.2025 Main goal The UEFA Football Division is seeking a passionate Data Scientist with expertise in spatial analytics to join our team. You will use advanced algorithms and data analysis to enhance decision-making and drive innovation in on-pitch and off-pitch football research. We’re looking for a self-starter with a deep enthusiasm for football and a commitment to advancing our data insights. If you’re excited about cutting-edge football analytics, we want to hear from you. Key Responsibilities Leading and contributing to innovative research in football analytics, exploring new methods and technologies to advance our understanding of on-pitch actions, the development of competitions and off-pitch trends. Overseeing the collection, cleaning and organisation of complex data sets to ensure scalable data pipelines, accuracy and usability for analysis. Working closely with team members and stakeholders to translate data findings into clear, actionable recommendations and to support data-driven strategies. Designing and implementing advanced algorithms and analytical models to extract actionable insights from on-pitch and off-pitch football data. Leading external agencies with the delivery of advanced analytics projects and integrating the methods for replication internally. Contributing to the evolution of the Unit in charge of the strategic development of the competitions. Performing quantitative analysis and developing mathematical tools and statistical models. Supporting the head of the Unit to build presentations to make the use of the data comprehensive for the end users. Requirements Experience At least 4 years of experience in data science using R and/or Python, preferably with sports or performance data. Experience with visualisation tools like Tableau or Dataiku is a plus; prior work with a sports organisation is an additional asset. Education Academic background in statistics, data science, sports analytics or a related field. Languages English: Proficient. Other requirements Knowledge of European football. Proficiency in Python for data manipulation and preparation, using Pandas, NumPy and Scikit-learn, with experience in spatial analytics and skeletal data using GeoPandas and Shapely. Expertise in data manipulation, preparation, and sports-specific modelling techniques. Familiarity with APIs, AWS (S3) and relevant data repositories. Knowledge of SQL or Snowflake is a plus. #J-18808-Ljbffr