Create client-facing analyses and reusable data products for Product, Analytics, Client Success, and Sales teams. Analyze large healthcare datasets to identify behavioral patterns among medical professionals, automate code, and communicate insights to technical and non-technical stakeholders. The role combines SQL, Python-based exploratory data analysis, data visualization, stakeholder collaboration, and opportunities to grow into presentation-focused or advanced technical work.

Lead statistical measurement and client intelligence initiatives using healthcare, prescription, and claims data. Develop performance benchmarks, evaluate program impact, apply statistical and machine learning methods, advise data scientists, support survey-based measurement, manage analytics vendors, mentor analysts, and present findings to marketing teams and clients. The role requires advanced SQL and Python, healthcare data expertise, vendor management, and extensive quantitative experience.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.