Evidation measures health in everyday life and enables anyone to participate in groundbreaking research and health programs. Built upon a foundation of user privacy and control over permissioned health data, Evidation's Achievement platform is trusted by millions of individuals—generating data with unprecedented speed, scale, and rigor. We partner with leading healthcare companies to understand health and disease outside the clinic walls. Guided by our mission to enable and empower everyone to participate in better health outcomes, Evidation is working to bring people individualized, proactive, and accessible healthcare—faster.
We’re looking for outstanding applied scientists who want to use machine learning on harness vasts 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.
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.
Build large scale machine learning 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 Machine Learning or at least 3 years of experience in building ML models
Extensive experience with TensorFlow, Keras or MXNet
Experience with unsupervised and semi-supervised deep learning (e.g., Variational Autoencoders)
Deep learning models for time series: WaveNet, UNet, DenseNet
Experience with weakly-supervised learning problems (incomplete, inaccurate, or inexact supervision)
Understanding of domain adaptation techniques.
Experience with probabilistic deep learning frameworks (TF Probability, Edward)
Health, dental, and vision benefits for you and competitive coverage for your family
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
EVIDATION HEALTH VALUES DIVERSITY AND IS COMMITTED TO EQUAL OPPORTUNITY FOR ALL PERSONS WITHOUT REGARD TO RACE, COLOR, CREED, RELIGION, MARITAL STATUS, AGE, NATIONAL ORIGIN OR ANCESTRY, POLITICAL ACTIVITY OR AFFILIATION, PHYSICAL OR MENTAL DISABILITY, MEDICAL CONDITION INCLUDING GENETIC CHARACTERISTICS, MARITAL STATUS, SEXUAL ORIENTATION, GENDER IDENTITY, SEX OR GENDER.