Company: Well-funded stealth company focused on disrupting healthcare through a differentiated consumer experience and a world-class data & analytics engine to drive engagement and behavior change. The product will sell directly to both Fortune 500 CEOs and full risk populations, integrating layers of analytics, digital, concierge services, behavioral health, telemedicine, care management and wellness services to drive sustained engagement, lower costs and improve health. A key differentiator to drive the company’s success will be a highly diverse, engaged organization whose employees are passionate about the mission of the company and whose management is passionate about the employees.
Head of Data Science and AI
- The overall goal is to engage consumers in differentiated ways that drive better health outcomes. As part of the Health Engine organization, the primary mission is to develop and enhance the modeling and optimization platform that delivers member recommendations to improve health, cost of delivery, and engagement.
- You will leverage a wide range of disparate data sources across healthcare (member, payor, employer, provider, partner). You will leverage a detailed understanding of epidemiology and experience finding causal effects in large longitudinal observational real world data or real world evidence.
- You will lead in the creation of operational causal models using current and emerging techniques including Bayesian methods. You will need to apply a deep theoretical understanding of statistics, and causal inference. Most importantly, you will teach and mentor others in these areas.
- You will collaborate across the organization to drive projects from beginning to end: frame business questions, research, prototype, produce production ready models, and share insights. You will work with engineering to ensure robust translation to production environments and create solutions that operate effectively at scale.
- 5+ years’ industry experience in statistical modeling focused roles.
- Advanced degree (MS or PhD) in a quantitative field such as Statistics, Computer Science, Physics, Economics, Mathematics, or similar. Strong grasp and theoretical understanding of statistics, particularly around Bayesian methods and applications in causal inference.
- Demonstrated experience using Python for building statistical models with a focus on causal inference and Bayesian methods (stan, pymc3, numpy, pandas, scikit-learn, etc.).
- Proficiency with SQL and databases. Experience using Unix/OSX from the command line, version control (git), and general software development best practices for contributing to a collaborative code base. Experience executing analyses in the cloud (GCP, AWS).
- Strong communication and collaboration skills required. Ability to communicate technical modeling concepts and relevant aspects of modeling platforms to non-technical audiences.
- Willingness to teach and mentor others across all technical skill areas and in knowledge of the healthcare domain. Ability to work in a start-up environment that is fast paced and maintain a focus on rapid prototyping of capabilities
- Background and experience in healthcare and/or consumer-facing domains involving behavior change
Additional Job Information
Well is on a mission to redefine the healthcare experience. This is an opportunity to re-shape healthcare for America. We are developing solutions to improve the quality and affordability of healthcare. We welcome team members who are passionate about that mission. We embrace diversity and are committed to building an inclusive team.