CPHAS Limited (Contactless Predictive Health Alert System) is a company based in Hong Kong-Shenzhen Innovation and Technology Park (HSITP). We develop advanced, contactless solutions for health monitoring and early risk detection which combine data science, sensor technologies and predictive analytics.
Join us a Data Scientist and you will play a central role in developing CPHAS’s core predictive system involving machine learning, big data and advanced statistical modelling.
Location: Hong Kong (HSITP).
Hours: Full time.
Salary: To reflect qualifications and experience.
Key Responsibilities
- Provide advanced analytics support including machine learning, big data, and statistical modelling across multiple functional areas.
- Advise on appropriate analytical models based on available data, technology and platforms.
- Collaborate with our senior team, stakeholders, partners and customers to develop and implement solutions.
- Develop machine-learning algorithms and models, providing technical recommendations.
- Develop, test and optimize advanced analytics and machine learning solutions.
- Monitor product performance and initiate improvements when needed.
- Ensure compliance with the highest data governance standards.
Requirements
- A degree in computer science, biochemistry, statistics or a related discipline.
- Strong analytical skills with the ability to understand algorithms and methodologies for complex problem-solving.
- Proficiency in Python and cloud stack.
- Knowledge of Spark, R, Hive, Hadoop, SQL and data visualization tools such as QlikView or Power BI is an advantage.
- Solid understanding of database concepts, data analysis and statistical/data modelling.
- Excellent communication skills to explain ideas and technical issues to colleagues and other stakeholders.
- Willingness to join and grow together with a young company; interest in building a business.
- Passion for AI, innovation and creating data-driven solutions.
- Background in or experience of healthcare.
- Availability to work in Hong Kong.
Closing Date
16 September 2026
Contact
Please send CVs and cover letters to [email protected]