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
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.
Contact
Benjamin Adler
HR Business Partner