Ro is a direct-to-patient healthcare company providing high-quality, affordable healthcare without the need for insurance. Ro is the only company to seamlessly connect telehealth and in-home care, diagnostics, labs, and pharmacy services nationwide. This is enabled by Ro’s vertically integrated platform that powers a personalized, end-to-end healthcare experience from diagnosis, to delivery of medication, to ongoing care. Since 2017, Ro has facilitated more than eight million digital healthcare visits in nearly every county in the United States, including 98% of primary care deserts. Ro also provides its patient-centric solutions including Workpath, its in-home care API, and Kit, its at-home diagnostic testing service, to other healthcare companies.

What You'll Do
Query electronic health record databases to create necessary data files for analytics
Create statistical analysis plans and lead analytical programming and execution to support high profile research and claims substantiation
Apply advanced quasi-experiemental statistical methods on observational data for the purpose of causal inference (e.g. propensity score matching, within-subject proportional hazards)Identify and implement appropriate models for longitudinal and repeated measures datasets
Conduct power analyses to determine appropriate sample and minimum effect sizes for studiesCreate documentation to support scientific publications, claims substantiation, and other dissemination as needed

What You'll Bring to the Team
MS or PhD in Biostatistics, Quantitative Methods, or related discipline (PhD preferred)
3+ years’ experience as a statistician in a health care setting
Proficiency in SQL and statistical modeling software including (R and/or Python)
Experience with big data
Experience with complex statistical modeling for causal inference and longitudinal analysis
Experience with power analyses
Excellent oral and written communication skills.
Strong collaborative skills and ability to work with a cross-functional team

Bonus points for:
Knowledge of obesity space
Comfort with data science fundamentals and applications
Experience with Git