Data Scientist (Machine Learning Engineer- CGM Algorithm Dev.)

Proclinical Staffing; Basel; Vor Ort; CHF 80’000 - 100’000; Vollzeit

Zusammenfassung

A leading life sciences recruiter is seeking a Data Scientist to develop and validate algorithms for Continuous Glucose Monitoring (CGM) systems. This role involves transforming sensor data into clinical insights, requiring proficiency in Python and a strong background in machine learning. Candidates with a Master's or PhD in a quantitative field are encouraged to apply. The position is located in Basel, Switzerland, and offers a collaborative, Agile team environment.

Qualifikationen

• Proven experience in developing machine learning algorithms.
• Strong background in statistical analysis.
• Ability to manage heterogeneous time series data.

Aufgaben

• Design and validate predictive algorithms for CGM data.
• Create efficient code for data processing and analysis.
• Collaborate in Agile teams to achieve project outcomes.

Kenntnisse

Proficiency in Python

Statistical principles

Experiential design

Machine Learning

Time series data analysis

Ausbildung

Master's or PhD in Data Science or related field

Tools

Pandas

NumPy

Scikit-learn

TensorFlow/PyTorch

XGBoost

Jobbeschreibung

Data Scientist (Machine Learning Engineer - CGM Algorithm Dev.)

Looking to uncover insights that could revolutionize the future of medicine and drive breakthroughs in patient care?

Proclinical is seeking a Data Scientist to contribute to the development and validation of innovative algorithms for Continuous Glucose Monitoring (CGM) systems. This role focuses on transforming complex physiological sensor data into meaningful clinical insights, integrating diverse datasets such as meal logs, insulin injections, and physical activity. The position requires a strong foundation in statistical analysis, machine learning, and creative problem-solving to evaluate and validate technical concepts effectively.

Please note that to be considered for this role you must have the right to work in this location or hold an EU passport.

Responsibilities

• Design, develop, and validate predictive and analytical algorithms for CGM data.
• Create robust code using advanced machine learning and statistical techniques to assess technical feasibility.
• Model potential algorithmic approaches based on patient needs and real-world sensor data.
• Process and manage heterogeneous time series data from medical devices, including data cleaning, imputation, transformation, and feature engineering.
• Build and optimize machine learning models (e.g., XGBoost, Neural Networks) and write efficient, reproducible Python code for analysis and experimentation.
• Provide technical guidance within an Agile team framework and collaborate with multidisciplinary teams to achieve project goals.
• Present complex technical results and feasibility findings clearly to diverse stakeholders.

Key Skills and Requirements

• Proficiency in Python and its core data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, XGBoost/LightGBM).
  
• Strong understanding of statistical principles, experimental design, and model validation techniques.
• Experience in processing, analyzing, and modeling time series data from physical sensors or monitoring devices.
• Background in Data Science, Machine Learning, Statistics, or a related quantitative field (Master's or PhD preferred).
• Ability to work effectively in a collaborative, multidisciplinary environment.

If you are having difficulty in applying or if you have any questions, please contact Ashley Bennett at [e-mail].

If you are interested in applying to this exciting opportunity, then please click 'Apply' or to speak to one of our specialists please request a call back at the top of this page.

Proclinical is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. Proclinical is acting as an Employment Agency in relation to this vacancy.

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