Senior Data Scientist 1

Summary

Join Zwift as a Data Scientist and collaborate on developing products and features that will grow the business. You will work with complex physiological datasets, design data collection experiments, and build AI/ML models to predict and classify fitness parameters. The role involves identifying and resolving model performance issues, analyzing user data to improve engagement, and evaluating ML tools. You will collaborate with cross-functional teams and communicate findings to non-technical stakeholders. A strong background in signal processing, physiological data analysis, and machine learning is required, along with experience in a data science role. Proficiency in Python and SQL is essential.

Requirements

• Bachelor's or Master's degree, or equivalent experience, in an applied field such as Engineering, Applied Physics, Applied Data Science or related topics, with specialisations such as Sports Analytics as a bonus
• 3+ years of experience in a Data Science role, with a strong preference for experience in biomechanics, wearables, health & wellness, or fitness sectors
• Proficient in Python and SQL for data manipulation, analysis, and model development
• Strong understanding and practical experience with various statistical techniques and machine learning algorithms (e.g., regression, classification, clustering, time series analysis, recommendation systems)
• Solid understanding of experimental design principles (A/B testing, multivariate testing), test sample sizes and statistical inference
• Experience with data visualization tools (e.g., Tableau, Looker, Matplotlib, Seaborn) to create clear and actionable insights
• Excellent self-directed, analytical and problem-solving skills with a curious mindset and a passion for extracting insights from complex datasets
• Strong verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders

Responsibilities

• Collaborate on the development, training, and evaluation of sophisticated AI/ML models (e.g., deep learning, time-series models, other modeling techniques) with a solid understanding of different signal processing techniques, to predict, classify, and quantify fitness parameters
• Work with complex physiological datasets, understanding the nuances of human performance, fitness levels and associated measurement data relationships
• Design and execute data collection experiments to gather data for model training and validation, and to evaluate changes and new features, often involving human subjects research
• Identify, diagnose/understand, AI/ML model performance, robustness and accuracy issues against established physiological benchmarks and real-world performance, and collaborate to make improvements
• Deep dive into user data to understand how users interact with the application, identify key engagement drivers, and pinpoint areas for improvement
• Evaluate different ML tools to understand relative technical advantages and disadvantages and provide clear informed recommendations to management
• Collaborate cross-functionally with Product, Engineering, Marketing, and Design teams to define problems, develop data-driven solutions, and ensure insights are integrated into product development cycles

Preferred Qualifications

• Experience with big data technologies (e.g., Databricks)
• Interest or experience of electronics design principles and embedded programming such as Arduino projects
• Experience of Open source/GitHub projects related to machine learning
• You will have an interest in fitness, health, and well-being, with an understanding of the bodies response to exertion levels, structured training processes, and performance metrics such as FTP, VO2Max, Power Curve and HRV
• You stay abreast with the latest research and advancements in physiological sensing, wearable technology, sports science, and machine learning