Data Scientist (all genders) - On-Site Presence

The company Behind every record, there are years of intensive training and the athlete’s desire to produce excellent performances. Behind the result, there is profound know-how and the high precision of Swiss Timing’s state-of-the-art technology. If you want to participate in the future development of high level sport events ... we are looking for you! Globally active, our company is constantly seeking for employees determined to progress and strive in a highly innovative environment. As a company of the Swatch Group, we are committed to quality of life, health and safety, and the environment. We are eager to hire employees with a sustainable mindset. Job description As a Data Scientist at Swiss Timing, you will play a key role in transforming raw sports data into meaningful insights that support performance analysis, data-driven decision-making, and data storytelling. Working as a core member of an interdisciplinary tech team, your primary mission is to develop advanced machine learning models, agentic systems, and AI-powered self-service analytics solutions that drive our live and post-processing systems across a wide range of sports. You will collaborate closely with data engineers, software developers, and sports domain experts to build robust analytics pipelines and AI-powered systems. This role requires strong scientific thinking, hands-on ML development, and a collaborative mindset to deliver reliable, sport-specific performance metrics. • Apply statistical analysis to complex datasets and develop, evaluate, and continuously improve supervised and unsupervised machine learning models • Develop agentic systems that interact with data sources and analytical tools • Build AI-powered self-service analytics solutions to create tailored analyses, visualizations, and actionable insights for athletes, federations, media, and internal stakeholders • Analyze and contextualize sports data to develop algorithms that compute key performance metrics • Partner with engineering teams to ensure databases used for ML and AI applications are clean, structured, and validated with robust data quality checks • Work closely with our technical and engineering teams to deploy, maintain, and monitor machine learning models in production • Contribute to innovation by exploring new methodologies and proactively improving existing AI and ML systems Profile • Strong analytical and conceptual thinking skills • High affinity for machine learning, generative AI, data-driven problem solving, and complex systems • Structured, independent, and solution-oriented working style • Ability to communicate complex data and insights in a clear and understandable way • Interest in sports and data-driven performance analysis • Detail-oriented and quality-focused • Team player with the ability to collaborate effectively in interdisciplinary environments • Curiosity and motivation to continuously learn and explore new technologies and methods Professional requirements • Degree in Data Science, Computer Science, Engineering, Mathematics, or a related field • Strong background in statistics and machine learning, including experience with supervised and unsupervised learning, and model evaluation. • Experience with LLM-based applications or agentic systems • Proficiency in Python; experience with SQL, C++, and C# is a plus • Experience with data visualization, scientific analysis workflows, and deploying models into production environments • Solid understanding of scientific methodology, testing, and experimental validation Languages • Good communication skills in English are required.