Principal Data Scientist

Who we are. . .

Pearl Health is restoring the independence and joy of practicing medicine for doctors in the United States. Our healthcare system has burdened our doctors with too much process, while removing them from what they do best: caring for those we love most. We are a team of physicians and public health experts (Stanford, Dartmouth, Harvard, Mass. General), technologists (athenahealth, Apple, Amazon, Meta, Flatiron, WalMart Health), healthcare innovators (Oscar, Aledade, VillageMD, Stellar, Arcadia) and experienced risk management professionals (CVS/Aetna, Humana, Cigna, United) who believe that primary care providers (PCPs) are the key to the United States’  future health. Pearl recently announced a strategic partnership to proliferate value-based care with Walgreens, one of the largest healthcare companies in the country. Our investors include Andreessen Horowitz, Viking Global Investors, AlleyCorp, and SV Angel. 

Pearl Health helps PCPs who are overwhelmed by the demands of an aging population and the unpredictable business model inherent to Traditional Medicare. Over time, this solution will empower PCPs to provide better care to their entire patient population. We believe there is a need to bring humanism back to healthcare by giving physicians the ability to better allocate their time with patients, increasing their autonomy, creating incentives that are aligned with achieving better outcomes through clinical decision-making powered by actionable intelligence, and making risk more available and more readily optimized through an intelligent marketplace. The Center for Medicare and Medicaid (CMS) is launching a new value-based care program to disrupt Traditional Medicare, and we believe that this represents an opportunity to achieve the meaningful change we envision.

The role. . .

We are seeking a highly skilled Principal Data Scientist who can perform and advise on technical analyses across the spectrum of research areas engaged by Pearl’s Data Science and Analytics team.  This work ranges from:

• patient risk stratification in order to determine which patients are in most urgent need of care, 
• application of causal analysis to determine the treatment effect of Pearl’s platform, 
• analyses in the vein of health economics to find “hot spots” of inefficient care management across our geographically dispersed and heterogeneous network of PCPs,  
• financial modeling of the economic outcomes of PCPs in a variety of VBC programs, and 
• the development of analytical pipelines and reporting to empower business stakeholders to make informed evidence-based decisions.  

Of course, we are not expecting to do all of these things in a given day or week, but the role will require you to rove among most, if not all, of these areas (and others) over the course of many months or quarters.  

This position will require that you function as an independent implementer of advanced quantitative research, an enabler and reviewer of the work of your colleagues,  an adviser to company leadership about initiatives which leverage data science and analytics,  a thought partner with internal business stakeholders, and a role model of sound quantitative research, for both members of the Data Science and Analytics team and the entire company.  Ideally, you have experience in a startup environment and with healthcare data.  Your willingness to dig into the nuances of different value-based care programs (e.g., ACO REACH, MSSP) and Medicare Advantage will be critical to success.

What Principal Data Scientist means to us...

• Deep expertise in many modern quantitative techniques (e.g., causal inference, deep learning, Bayesian analysis, stochastic simulation).  While no one can have deep knowledge of more than a few advanced techniques, we expect that you can quickly assimilate sufficient knowledge of almost any quantitative method in order to assist a colleague with their research, evaluate the rigor, applicability, or correctness of the research, or to advise leadership on how to develop or acquire the resources needed to leverage the method.  
• Similarly flexibility and adaptability to conduct analyses using a variety of data sources.  This work would include articulating the potential value of new or previously unidentified data sources to our business or research needs.
• Balance the need to carefully study a problem space to produce sound evidence-based conclusions with the need to deliver impact-oriented results in a dynamic business environment.
• Provide strategic direction and thought leadership in the development and execution of data science initiatives and collaborate with cross-functional teams to identify business opportunities and drive data-driven decision making.
• Savor rolling up your sleeves to conduct hands-on data