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Biomedical Data Science Engineer - Health Technologies
Apple
H1B ✓On-sitemid levelPosted April 14, 2026
About the Role
Collaborate with multidisciplinary teams to design and validate physiological models, algorithms, and sensor-based health technologies. Develop analysis tools and visualization strategies to interpret complex physiological time-series data and influence project decisions.
Requirements
Requires an MS or PhD in Biomedical Engineering or a related field with strong experience in physiological sensors and data analysis. Proficiency in Python and experience with data visualization and modeling tools are essential.
Full Job Description
The Health Technologies Team conceives and proves out exciting new technology for Apple’s future products and features. In this role, you can be involved in the end-to-end new product development cycle for health and wellness technologies, from product ideation and feasibility assessment to algorithm implementation and product validation. Join our team to create extraordinary features that represent the cutting edge of innovation in the dynamic consumer health field.
In this role, you’ll collaborate with multidisciplinary teams to create innovative health products and features. As a biomedical data scientist, your responsibilities will include: -design and support of lab and human studies ranging from small scale pilot investigations to large scale sensor fusion studies -distill and interpret study findings to assess system performance and confounders -define and evaluate sensor feasibility criteria, including KPI development, mapping user experience requirements to sensor specifications -develop analysis tools to evaluate and interpret physiological time series sensor data -design, implement, and validate physiological models and algorithms -develop data visualization strategies for sharing complex data and study findings to influence project decisions and direction. The role requires effective collaboration with team members spanning a broad range of expertise and disciplines. Flexible thinking, adaptability to change, comfort with ambiguity, and ability to work both independently as well as in a team setting are hallmarks of success on our team.
MS in Biomedical engineering or other engineering discipline with relevant prior experience with time-series physiological sensors, devices, and applications. Must have a strong understanding of human physiology coupled with experience in the use of multi-sensor systems to measure, characterize, and analyze time-series physiological signals. Must have experience using Python to process, analyze, and visualize data. Must be facile with the corresponding Python tools (e.g., matplotlib, plotly, tableau, etc.). Must be highly organized and able to thrive in a fast-paced environment. Must have excellent communication skills.
PhD in Biomedical engineering or other engineering discipline with relevant prior experience. Experience with deep learning frameworks (e.g., PyTorch) including model training, loss function design, optimization, and cross-validation. Experience with statistical testing methods and their application to experimental data analysis. Experience with distributed processing frameworks (e.g., Spark, Dask) for large-scale data workflows. Experience with data management, organization, storage, and retrieval.
Description
In this role, you’ll collaborate with multidisciplinary teams to create innovative health products and features. As a biomedical data scientist, your responsibilities will include: -design and support of lab and human studies ranging from small scale pilot investigations to large scale sensor fusion studies -distill and interpret study findings to assess system performance and confounders -define and evaluate sensor feasibility criteria, including KPI development, mapping user experience requirements to sensor specifications -develop analysis tools to evaluate and interpret physiological time series sensor data -design, implement, and validate physiological models and algorithms -develop data visualization strategies for sharing complex data and study findings to influence project decisions and direction. The role requires effective collaboration with team members spanning a broad range of expertise and disciplines. Flexible thinking, adaptability to change, comfort with ambiguity, and ability to work both independently as well as in a team setting are hallmarks of success on our team.
Minimum Qualifications
MS in Biomedical engineering or other engineering discipline with relevant prior experience with time-series physiological sensors, devices, and applications. Must have a strong understanding of human physiology coupled with experience in the use of multi-sensor systems to measure, characterize, and analyze time-series physiological signals. Must have experience using Python to process, analyze, and visualize data. Must be facile with the corresponding Python tools (e.g., matplotlib, plotly, tableau, etc.). Must be highly organized and able to thrive in a fast-paced environment. Must have excellent communication skills.
Preferred Qualifications
PhD in Biomedical engineering or other engineering discipline with relevant prior experience. Experience with deep learning frameworks (e.g., PyTorch) including model training, loss function design, optimization, and cross-validation. Experience with statistical testing methods and their application to experimental data analysis. Experience with distributed processing frameworks (e.g., Spark, Dask) for large-scale data workflows. Experience with data management, organization, storage, and retrieval.