Senior Data Scientist, Provider Data Science

Thyme Care Thyme Care · Healthcare · Remote · Data Science

This role focuses on building and maintaining analytic capabilities within Thyme Care's Data team. The Senior Data Scientist will model data, create visualizations, and deliver insights to drive action. Key responsibilities include improving data pipelines, designing scalable data architecture and healthcare data models, establishing KPIs and reporting standards, and partnering with stakeholders to translate business requirements into technical plans. The role requires deep experience with healthcare data, expertise in analytics, data modeling, data transformation, dbt, and SQL, and experience with large healthcare datasets.

What you'd actually do

  1. Gain a deep understanding of our core data architecture and lead improvements to our data pipelines, balancing near-term needs with long-term architectural health.
  2. Own and lead the development of data models that make it possible to analyze the nuances of our EMR drug delivery and drug economics in ways that scale across contracts and pharmacy interventions.
  3. Establish key KPIs and reporting standards that help stakeholders make our operations more efficient.
  4. Partner with stakeholders to understand and translate their business requirements into technical plans. This involves developing data models, pipelines, and analytics dashboards. For example, you own the end-to-end data life cycle of data ingestion from a practice, standardization and cleaning, core modeling and BI dashboarding for both internal and external partners.
  5. Lead the development of utilization and quality metrics and serve as a domain expert for stakeholders across the company. Additionally, you will leverage our data assets for business opportunities and strategic initiatives at Thyme Care.

Skills

Required

  • SQL
  • dbt
  • data modeling
  • data transformation
  • analytics
  • healthcare data (EMR, claims, prior auth)

Nice to have

  • Python
  • R
  • Looker
  • drug data
  • Medicare Part D data

What the JD emphasized

  • Deep experience working with healthcare data such as electronic health records, claims, or prior auth.
  • Deep expertise in dbt and SQL, with experience designing, rebuilding, and owning complex data models and pipelines that ensure reliability and scalability across the data platform.
  • Experience with large healthcare datasets, ideally in a healthcare-focused technology startup, health plan, or provider group with mature data structures and pipelines.