Our client, a key player in the industry, is looking for a Data Scientist to drive the feasibility evaluation, prototyping, design, and validation of novel algorithms for Continuous Glucose Monitoring (CGM) systems.

Responsibilities:

• Translate complex physiological sensor data into accurate, clinically relevant insights
• Integrate and interpret diverse sensor and log data related to meal, insulin injections and physical exercise
• Understand patient needs and creatively model potential algorithmic approaches using real-world sensor data
• Execute rigorous data cleaning, imputation, transformation, and sophisticated feature engineering
• Build and optimize machine learning models (e.g., XGBoost, Neural Networks, etc.). Write high-quality, efficient, and reproducible Python code for data analysis, modeling, and experimentation

Requirements:

• Master or PhD in Data Science, Machine Learning, Statistics, or a related quantitative field
• At least 5 years hands-on experience as a Data Scientist or Machine Learning Engineer
• Strong proficiency in Python and its core data science ecosystem: Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, and XGBoost/LightGBM
• Solid grasp of statistical principles, experimental design, and model validation techniques
• Practical experience with the processing, analysis, and modeling of time series data from physical sensors or monitoring devices

If you want to learn more about this opportunity apply directly or reach out to [email protected]

*Please note that we can only consider EU/Schengen applications, or valid Swiss permit.