Biomedical Data Science Engineer - Health Technologies

Apple Apple · Big Tech · San Diego, CA +1 · Hardware

This role focuses on biomedical data science within Apple's Health Technologies team, involving the end-to-end development of health and wellness features for future products. Responsibilities include designing and supporting studies, interpreting findings, defining sensor feasibility, developing analysis tools for physiological time series data, and implementing/validating physiological models and algorithms. The role requires collaboration with multidisciplinary teams and a strong understanding of human physiology and multi-sensor systems. Experience with Python for data analysis and visualization is mandatory, with preferred experience in deep learning frameworks, statistical testing, and distributed processing.

What you'd actually do

  1. design and support of lab and human studies ranging from small scale pilot investigations to large scale sensor fusion studies
  2. distill and interpret study findings to assess system performance and confounders
  3. define and evaluate sensor feasibility criteria, including KPI development, mapping user experience requirements to sensor specifications
  4. develop analysis tools to evaluate and interpret physiological time series sensor data
  5. design, implement, and validate physiological models and algorithms

Skills

Required

  • MS in Biomedical engineering or other engineering discipline with relevant prior experience with time-series physiological sensors, devices, and applications.
  • Python
  • matplotlib
  • plotly
  • tableau

Nice to have

  • PhD in Biomedical engineering or other engineering discipline with relevant prior experience.
  • PyTorch
  • model training
  • loss function design
  • optimization
  • cross-validation
  • statistical testing methods
  • Spark
  • Dask
  • data management
  • organization
  • storage
  • retrieval

What the JD emphasized

  • 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 highly organized and able to thrive in a fast-paced environment.
  • Must have excellent communication skills.

Other signals

  • develop analysis tools to evaluate and interpret physiological time series sensor data
  • design, implement, and validate physiological models and algorithms
  • Experience with deep learning frameworks (e.g., PyTorch) including model training, loss function design, optimization, and cross-validation.