Digital Health

Senior Scientist – Mobile Health

Position Overview

At Sage Bionetworks, we believe that we can learn more by learning from each other. By improving the way scientists collaborate, we help to make science more effective. We partner with researchers, patients, and healthcare innovators to drive collaborative data-driven science to improve health. Making science more open, collaborative, and inclusive ultimately advances biomedicine.

Are you the type of person who enjoys engaging with scientists and researchers across many disciplines? Do you have the ability to develop statistical and machine learning models to address computational problems in the area of mobile health? Do you want to be an integral part of a team that includes computational biologists, machine learning scientists, research ethicists, software engineers, and data librarians? If so, you could be our next Senior Research Scientist on the Mobile Health (mHealth) team. You would bring your expertise in data processing, statistical analysis, machine learning, and human health to extract meaningful insights from mobile and sensor data.

Specific Responsibilities Include

Using quantitative analysis, signal processing, data mining and machine learning to analyse large amounts of sensor data from smartphones, wearables and other devices.
Establishing the biological, clinical, and participant relevance of sensor data collected in digital health studies.
Contributing to the improvement and automation of data processing and analysis pipelines across different mHealth studies.
Designing and evaluating experiments to collect relevant digital endpoints.
Building and analyzing dashboards and reports for external communications.
Writing peer-reviewed journal articles to establish the biological and clinical significance of data collected in mHealth studies.

Basic Qualifications

Are passionate about open science and collaboration.
Are passionate about digital health technologies.
Have an MS or PhD in a quantitative discipline (e.g., statistics, computational biology, biomedical engineering, computer science, applied mathematics, or similar), or another scientific degree with commensurate experience.
Have at least an additional 2 years of experience in an analytical role developing both statistical and machine learning models.
Are proficient at extracting, cleaning, and analyzing physiological or mobile sensor data sets using data/statistical tools such as R, Python, MATLAB, or similar.
Have practical knowledge of digital signal processing and analysis of time-series data.
Have expertise in exploratory and statistical data analysis (such as linear models, multivariate analysis, predictive modeling, and stochastic models).
Demonstrate a track record of writing compelling publications in high impact, peer reviewed journals.
Enjoy teaching others and learning new techniques.
Are a strong communicator (oral and written).

Preferred Qualifications

Familiarity with Deep Learning frameworks (Keras, TensorFlow, PyTorch etc.) is preferred.
Experience with the analysis of sensor data from wearables or mobile sensors and clinical data is preferred
Familiarity with software engineering practices and experience developing production software is preferred.

About Sage Bionetworks

Sage Bionetworks is a nonprofit biomedical research and technology development organization that was founded in Seattle in 2009. Our focus is to develop and apply open practices to data-driven research for the advancement of human health. Data-driven research has become an important component of biomedicine, but it’s not always easy to understand how to apply computational approaches appropriately or how to interpret their results. Sage believes open practices can help. Our interdisciplinary team of scientists and engineers work together to provide researchers access to technology tools and scientific approaches to share data, benchmark methods, and explore collective insights, all backed by Sage’s gold-standard governance protocols and commitment to user-centered design. Sage is supported through a portfolio of competitive research grants, commercial partnerships, and philanthropic contributions.

Apply Now