About the role
About OpenLoop OpenLoop was co-founded by CEO, Dr. Jon Lensing, and COO, Christian Williams, with the vision to bring care anywhere. Our telehealth support solutions are thoughtfully designed to streamline and simplify go-to-market care delivery for companies offering meaningful virtual support to patients across an expansive array of specialties, in all 50 states.
About
The Role OpenLoop’s mission is to bring care anywhere by powering telehealth solutions at scale. OpenLoop is seeking a Staff Data Analyst to support the growth on our Business Intelligence team. This role will serve as an analytical partner across our growing healthcare organization. They will be responsible for shaping how data informs executive decision-making, operational excellence, regulatory compliance, and patient outcomes across our national tele-health platform. As a senior individual contributor, this role combines advanced analytics expertise with strong business partnership. Important - Please Read: If your experience is primarily with pre-packaged data or systems, this likely isn’t the right fit. You should be able to interpret, organize, and integrate data from multiple sources, and demonstrate how you use SQL to clean and structure it in a clear, efficient way. This role requires hands-on, day-to-day use of SQL in an advanced developer capacity. Although a Staff level Analyst may have leadership skill and experience, ALL of our analysts are still using SQL daily and often. As part of the interview process, a skill assessment will be conducted to evaluate your SQL proficiency and analytical reasoning. What You’ll Do: Define, and drive analytics strategy, in partnership with executive leadership Shape long-term KPI frameworks tied to patient outcomes, provider performance, compliance metrics, and operational scalability. Support regulatory reporting needs and ensure analytical frameworks will align Use SQL developer skills, you will often / daily, clean, organize and analyze data. to provide trends, patient engagement, provider performance, and quality measures. We are expecting you to know how to do this outside of the use of AI tools, in order to evaluate data quality. Ensure alignment across data definitions, reporting structures, and metric calculations. Identify risks related to accuracy, audit readiness, and healthcare
