Data Scientist (All Genders) - On-Site Presence

Job description

Data Scientist in Swiss Timing will play a key role in transforming raw sports data into meaningful insights that support performance analysis, data-driven decision making, and data storytelling. Your primary mission is the refinement, interpretation, and advanced analysis of measured sports data, contributing to both live and post-processing systems used across a wide range of sports and technologies.

You will work with signal processing, statistical analysis, and machine learning, developing robust algorithms and analytics pipelines that convert sensor data into reliable, sport-specific performance metrics. This role requires strong scientific thinking, hands-on algorithm development, and close collaboration with interdisciplinary teams.

• Design, implement, and maintain data processing pipelines and algorithms for live and post-event analytics across firmware and software stages
• Apply signal processing techniques (e.g. filtering, smoothing, resampling) and implement position estimation using Real Time Tracking System, computer vision, and IMU data
• Analyze and contextualize sports data; develop activity recognition algorithms and compute key performance metrics (e.g. speed, acceleration, jump height, rotation)
• Extract and communicate actionable insights for athletes, federations, and media
• Apply statistical analysis to complex datasets and develop, evaluate, and improve machine learning models (supervised & unsupervised)
• Create tailored analyses and visualizations for internal and external stakeholders
• Ensure data quality through systematic testing, validation, and performance monitoring; enhance robustness and reliability of outputs
• Contribute to innovation by developing new systems, analytics pipelines, and continuously improving existing technologies

Profile

• Strong analytical and conceptual thinking skills
• High affinity for 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, especially when working with sensitive data
• Team player with the ability to collaborate effectively in interdisciplinary environments
• Curiosity and motivation to continuously learn and explore new technologies and methods
• Proactive mindset with a drive to improve and innovate existing solutions

Professional requirements

• Degree in Data Science, Computer Science, Engineering, Physics, Mathematics, or a related field
• Strong background in statistics, machine learning, and signal processing
• Proficiency in Python; experience with C++ or C# is an advantage
• Experience with data visualization and scientific analysis workflows
• Solid understanding of scientific methodology and experimental validation
• Ability to work independently on complex analytical problems while collaborating effectively in a team

Languages

• Good communication skills in English are required.