The ideal candidate should have the passion to use data from biosensors and advanced machine learning techniques for making sense of biosensor data. We are building an end-to-end service that integrates seamlessly into the lives of those patients via multiple touchpoints on front-end while providing intelligent analytics on the backend.Responsibilities:
- Research and development of algorithms to detect abnormal subtle changes in physiology using biosensor data in real-time.
- Research and development of algorithms to derive clinical derivative parameters from continuous biosensor data including building disease specific models for patient's health deterioration.
- Design and architect the entire workflow of the algorithms that includes data inputs, outputs and database storage.
- Optimize data analysis processes and systems for better efficiency and maintenance.
- Conduct epidemiological research to analyze the patterns, causes and effects of health and disease in the cohort of collected patient data.
- Documentation which clearly explains how algorithms have been implemented, verified and validated.
- Draft and apply paper publications.
- Review task-related research database.
- Edit or review task-related research documents.
- Edit or review task-related develop documents.
- Hands on experience with development of end-to-end data analytics solutions including data exploration/crawling, personalized machine learning model building and performance evaluation.
- Knowledge in big data technologies including cloud computing/distributed computing and data visualization.
- Background in or exposure to healthcare data, human physiology or cardiology is good to have
- Proficient with time-series data analysis, anomaly detection, unsupervised learning, hypothesis testing.
- Proficient with programming in Python. Good in Programming in R or C/C++ is a plus.
- Good research ability and critical thinking skills.
- Masters or PhD in Bioinformatics, Statistics, Engineering or related fields with statistical modelling and machine learning skills.