Swiss Timing Data Scientist
About Swiss Timing
Swiss Timing stands at the intersection of Swiss precision, technological innovation, and world-class sport. As a member of the Swatch Group, the company has built an exceptional reputation for delivering timing, scoring, data handling, and broadcast solutions for the Olympic Games and leading international competitions. As an employer, Swiss Timing offers a dynamic environment where engineers, project leaders, technicians, and digital specialists contribute to moments watched by millions. The company values accuracy, reliability, teamwork, and calm excellence under pressure, providing employees with the opportunity to work on complex global events while advancing the standards of performance measurement in elite sport.
Swiss Timing seeks a Data Scientist in Leipzig to develop ML models and AI systems for sports performance analysis. On-site role.
Role & Responsibilities
- 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 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
Qualifications
- 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
Skills
Experience
Experience developing and deploying machine learning models in production environments, with demonstrated expertise in both supervised and unsupervised learning approaches. Background in applying statistical analysis to complex datasets and building analytics pipelines is essential. Familiarity with LLM-based applications or agentic systems is highly valued.
Education
Degree in Data Science, Computer Science, Engineering, Mathematics, or a related field.
Workplace
This position is based in Leipzig, Saxony, Germany.
Culture
Swiss Timing offers a workplace culture defined by precision, innovation, and the excitement of world-class sport. As part of the Swatch Group, it brings together technical expertise, teamwork, and operational excellence, giving employees the opportunity to contribute to high-profile international events where reliability and performance are essential.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Swiss Timing, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Machine Learning Engineer», «Sports Analytics Specialist», «AI Systems Developer», «Performance Analytics Engineer», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.