For our client we are looking for a highly skilled Machine Learning. The person in this role will be responsible for developing and optimizing ML models for analyzing data from breath sensor devices, working with time-series data, and applying signal processing techniques in clinical trials.
responsibilities :
Develop and optimize machine learning models for binary and multi-class classification in clinical trials.
Work with time-series sensor data from Breath analyzer sensor devices.
Apply signal processing techniques to denoise and preprocess sensor traces.
Optimize models for different metrics such as accuracy, sensitivity and specificity.
Contribute to the automation of data ingestion and processing.
Collaborate with data engineers, software developers, and clinical researchers to integrate machine learning models into clinical workflows.
Document methodologies and results for regulatory and investor presentations.
requirements-expected :
Academic degree in Machine Learning, Data Science, Electrical Engineering, Physics, or a related field.
Strong Python skills, with experience in Scikit-Learn, TensorFlow, PyTorch, or equivalent ML frameworks.
Expertise in signal processing and time-series analysis.
Knowledge of feature engineering and statistical analysis.
Strong understanding of model validation techniques.
