Junior Data Scientist - Preventive Health AI

About the role

Actxa, a deep tech company headquartered in Singapore, uses artificial intelligence to create preventive healthcare solutions covering physical activity, sleep, body composition, stress and recovery, heart health and blood glucose monitoring. This Junior Data Scientist role works in the R&D team with software engineers and research partners to turn wearable sensor data and health datasets into reliable insights, and to build generative AI features such as personalized health insights and conversational coaching.

Key responsibilities

• Research, develop and validate the algorithms and AI models behind Actxa's preventive health insights
• Turn wearable sensor data (PPG, accelerometer, heart rate variability) into insights on activity, sleep, stress, recovery and heart health
• Build and improve models for blood glucose estimation and nutrition, including food recognition and nutrition data pipelines
• Develop generative AI and LLM-based features such as personalized health insights, conversational coaching and behavioral nudging
• Help design and run research studies with clinical and academic partners, covering protocol preparation, data collection and data quality checks
• Clean, organize and analyze health datasets using statistical modelling, machine learning and deep learning
• Test and validate algorithm outputs against reference data and document methods and results
• Work with software engineers to bring models into Actxa's apps and products
• Use AI-assisted tools in day-to-day work while critically validating their outputs
• Contribute to research publications and invention disclosures

Required profile

• Bachelor's or Master's degree in Data Science, Computer Science, Computer Engineering, Biomedical Engineering, Statistics or a related discipline
• 0 to 2 years of relevant experience; fresh graduates with strong internship or project experience are welcome
• Ability to explain findings clearly to non-technical colleagues
• Positive, adaptable and able to work in a small team where priorities can shift

Required skills

• Good working knowledge of Python and SQL, and libraries such as pandas, NumPy, scikit-learn and PyTorch or TensorFlow
• Solid foundation in statistics and machine learning
• Plus: signal processing or time-series data from wearables, LLMs, prompt engineering or frameworks such as Hugging Face, LangChain or LLM APIs, exposure to clinical or health research, and keen interest in digital health and preventive healthcare