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 to fill multiple positions with outstanding applied scientists and engineers who want to use analytics and 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 candidates could have disciplinary training from several disciplines (machine learning, biostatistics, signal processing) and experience building models and applications from biomedical time series data.
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 impact of missing data and imputation techniques
- Communicate with a team of data scientists drawing from a very diverse set of expertise
- 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
- PhD in biomedical engineering, electrical engineering, data science, computer science, biostatistics, or related discipline, OR
- Masters in biomedical engineering, electrical engineering, data science, computer science, biostatistics, or related discipline with 2+ years of industry experience
- Experience in health data science or related fields (academics OK)
- Proficiency in Python, Matlab, or R
- 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
- Strong foundation on software engineering best practices
- Experience working with biomedical time-series data
- Experience with extracting features from wearable sensors
- Knowledge of deep learning frameworks: Keras and TensorFlow
- Understanding of statistics: significance tests, source of biases, mixed effect models, experiment design
- 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