Data Scientist for CGM Algorithm Development
Roche Switzerland bridges the gap between pharmaceuticals and diagnostics. Important research and development functions are located here. For our long-term client, F. Hoffmann-La Roche AG in Basel, we are looking for a Data Scientist for CGM Algorithm Development.
Background:
The Data Scientist will drive the feasibility evaluation, prototyping, design, and validation of novel algorithms for Continuous Glucose Monitoring (CGM) systems. This role is instrumental in translating complex physiological sensor data into accurate, clinically relevant insights, integrating and interpreting diverse sensor and log data related to meals, insulin injections, and physical exercise. A strong blend of statistical rigor, machine learning expertise, and creative problem-solving is required to evaluate and prove the technical viability of promising clinical concepts.
The ideal candidate will have a minimum of 5 years of hands-on experience as a Data Scientist or Machine Learning Engineer and must be fluent in English. A robust academic background in Data Science, Machine Learning, or Statistics (Master's or PhD is highly desirable) is also a key requirement.
Tasks & Responsibilities:
- Algorithm Design & Prototyping: Design, develop, and validate predictive and analytical algorithms for CGM data. Develop robust code using advanced ML and statistical techniques to demonstrate technical feasibility.
- Feasibility & Ideation: Understand patient needs and creatively model potential algorithmic approaches using real-world sensor data.
- Data Pipeline & Feature Engineering: Apply expertise in processing and managing heterogeneous time series data from medical devices. Execute rigorous data cleaning, imputation, transformation, and sophisticated feature engineering.
- Technical Execution & Modeling: 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.
- Collaboration: Provide technical guidance within an Agile team framework to junior data science colleagues. Work effectively within a multidisciplinary, distributed team to translate project goals into actionable data science tasks.
- Communication & Reporting: Synthesize complex technical results and present clear feasibility findings to diverse stakeholders.
Must Haves:
- Minimum of 5 years of hands-on experience as a Data Scientist or Machine Learning Engineer.
- Demonstrated experience or a robust academic background (Master's or PhD) in Data Science, Machine Learning, Statistics, or a related quantitative field.
- Strong Statistical Foundation: Solid understanding of statistical principles, experimental design, and model validation techniques.
- Advanced Python Proficiency: Strong proficiency in Python and its core data science ecosystem: Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, and XGBoost/LightGBM.
- Time Series Data: Practical experience with the processing, analysis, and modeling of time series data from physical sensors or monitoring devices.
Nice to Have:
- Medical Domain Knowledge: Prior experience working with medical data, specifically in diabetes management (CGM/BGM), exercise physiology, or clinical nutrition data.
- Regulated Environment: Familiarity with the requirements and processes for software development in a regulated medical device environment.
- Big Data Tools: Experience with distributed computing frameworks like PySpark for handling very large datasets.
What You Will Be Offered:
- An opportunity to work in one of the world's leading pharmaceutical companies.
- Modern campus with plenty of green spaces and meeting areas.
- Central location in Basel.
- Varied job profile.
- Further training opportunities through temptraining.
- Working in a dynamic and motivated team.
If you are interested, please apply online using the form below. Only applications matching the job profile will be considered.