As a Senior Data Scientist, you will help us apply statistical and machine learning techniques to complex health datasets to predict feature engagement, behavioral change, and health outcomes and challenge the state of the art personalization techniques in the domain of health and wellness. In this role, you will work as part of a small multi-disciplinary data science team that focuses on using data based methods to personalize the user experience and research the impact that our platform has on user health. This team will not only work with the product team (and in some cases embed directly in a product team) closely but will also support non-user-facing functions like Business Strategy and Partners.

To thrive in this role, you are someone who works well in cross-functional teams and enjoys collaborating. Furthermore, you understand the business impact of your work and enjoy measuring and presenting it. You enjoy working with product management and other stakeholders to find the best solution to the problem at hand, iterate over it and can balance technical complexity with delivering customer value in a timely fashion.

Our current data pipelines are built with Airflow and Python, we extensively leverage GCP capabilities (e.g. Cloud Functions, Vertex AI, Healthcare API, BigQuery) and utilize the Fast Healthcare Interoperability Resources standard across our data platform and to model our operational data. You will tackle complex health and non-health related datasets ranging from client events from our mobile applications, self-reported health information, connected devices data, and data from traditional healthcare systems of record (e.g. claims, care gaps, EHR).


In this role, you will:

• Effectively utilize statistical and machine learning algorithms in building personalization services including but not limited to recommendation engines and other predictive models that can be used to personalize the end-user in-app experience. 
• Your work will include identifying and engineering features (including collaboration with stakeholders to inform appropriate features and target labels), evaluation of various modeling techniques to employ, development of said models, and collaboration with machine learning engineers to put your models into production and monitor their performance over time. 
• Collaborate with both internal and external stakeholders to understand health and insurance ecosystems, model user behaviors and other long-term wellness trends to inform your development of personalization services 
• Apply proven analytic methods and algorithms on cross-functional domains by sourcing and leveraging data to support modeling
• Conduct data based (e.g. primarily retrospective observational) research on our platform’s impact on user health as well as the application of data science and machine learning to digital health

About you:

• MSc or PhD focused on data science/machine learning research or applications
• 2+ years of experience in data science or machine learning engineering
• 2+ years building and shipping data science based personalization services and recommendation systems
• OR BSc focused on data science/computer science/engineering and  4+ years experience developing and shipping production grade machine learning systems 
• You have strong analytical and data science skills and are excited to apply it in non-traditional domains
• You know how to break down complex and ambiguous problems to smaller, more manageable sub-problems and iteratively deliver value to customers 
• You have deep experience with data science toolkits like scikit-learn, Keras and Tensorflow, including Python or R. You are eager to learn from others and help others grow with you