Data Scientist – Machine learning


  • Research and development of algorithms to detect abnormal subtle changes in physiology using biosensor data in real-time. 
  • Research and develop algorithms to process raw sensor data, such as accelerometer, gyroscope, PPG and ECG. 
  • 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. 
  • Work with APP developer and backend engineers to deliver the product.
  • Documentation which clearly explains how algorithms have been implemented, verified and validated. 


  • Masters or PhD in Bioinformatics, Statistics, Engineering or related fields with strong statistical modelling and machine learning skills.
  • Hands on experience with development of end-to-end data analytics solutions including data exploration/crawling, model building and performance evaluation. 
  • Proficient with programming in Python. 
  • Strong programming in C/C++ is a plus.
  • Knowledge in big data technologies including cloud computing/distributed computing and data visualization. 
  • Background in or exposure to healthcare data, sensor data, human physiology is a plus. 
  • Good publication records on novel algorithm development.
  • Strong problem-solving skills.
  • Excellent written and verbal communication skills, including the ability to communicate technically and non-technically with ability to translate between the two.


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