Evidation Health is a new kind of health and measurement company that provides the technology and guidance to understand how everyday behavior and health interact. The volumes of behavior data generated from wearables and smartphones has opened up new ways to analyze individuals’ behavior and health in real time. With a virtual pool of 3 million research participants, Evidation Health undertakes research for innovative biopharma and health care companies to transform how diseases are identified, treated, and monitored.
We’re looking for outstanding applied scientists and engineers who want to use digital signal processing to understand and harness vast amounts of multi-variate time series data from connected wearables, sensors, and other mobile data in order to infer changes in health status and disease progression over time. The ideal candidate would have experience working with biomedical time series data and in-depth knowledge of state-of-the-art digital signal processing methodologies.
We value problem-solving skills and an attitude towards learning: Our work lies at the intersection of many diverse fields including machine learning, signal processing, and epidemiology. We seek great communication and accountability, people who think people first.
If you thrive on autonomy and open-ended challenges, this is the perfect opportunity to take your career to the next level.
We have offices in San Francisco, San Mateo, and Santa Barbara, and are considering candidates for all three offices, as well as remote.
- Analyze continuous signals from biomedical devices to extract features predictive of health outcomes
- Understand the impact of missing data and imputation techniques
- Mentor a team of data scientists drawing from a very diverse set of expertise
- Communicate findings, roadblocks and timelines cross-functionally to ensure program objectives are met
- Build re-usable tools and models to predict health-related variables from time-series continuously collected from connected devices and apps
- Work with a team of data scientists with very diverse backgrounds and expertise to define tasks and performance metrics
- Maintain the highest level of rigor and develop best practices to build reproducible, generalizable, fair, unbiased, and preferably interpretable models
- PhD in biomedical engineering, electrical engineering, computer science, or related fields
- 3+ years experience in health data science or related field(s)
- Proficiency in Python, Matlab, or R
- Working knowledge of advanced signal processing methodologies (e.g. Fourier analysis, wavelets, Kalman filtering, nonstationary signal analysis, etc)
- High level of motivation and willingness to learn new tools and ideas. Health Data Science is a nascent field where methods and concepts are quickly evolving
- Working knowledge of machine learning and related processes
- Understanding of statistics: significance tests, source of biases, mixed effect models, experiment design
- Experience with extracting features from wearable data
- Health, dental, and vision benefits for you and competitive coverage for your family
- Relocation support
- Flexible work hours
- Open vacation policy - take time when you need it
- Support for remote work when needed
- Relaxed work environment
- Your choice of computing equipment and gear
- Lots of opportunities for growth
- Opportunity to work on fascinating challenges that improve people’s lives