Senior Data Scientist, Data Ingestion & Care Enablement

Thyme Care•Remote, United States

2d•$166,500 - $185,000

About The Position

As a Senior Data Scientist, you will join our Data team to help us build and maintain strong analytic capabilities supporting Thyme Care’s mission. In this position, you will collaborate closely with our Product Manager and our Growth and Operations teams to understand, ingest, and accurately model healthcare data for new and existing customers, supporting updates and fixes throughout the life of the relationship. You’ll develop novel attributes and flags from our existing data to drive action on our Care Team, and build visualizations to report on their impact. In the course of your work you should also expect to: Gain a deep understanding of our data platform and contribute to improving our data models and pipelines using SQL and dbt Collaborate with other data scientists, data engineers, and analysts to build scalable and sustainable data models and pipelines Transform incoming eligibility, claims, prior auth, and ADT data to fit into our standard data models, identifying data quality issue or proposed standard data model enhancements as needed Translate business requirements into technical plans so you can design data models, pipelines, and analytics before you begin building them Build relationships with data teams at risk-bearing entities (insurers, ACOs, PCPs, etc.) and demonstrate Thyme Care’s expertise in building data & analytics products Ensure that internal customers have fast, accurate, and reliable access to data, supporting their decision-making and operations with high-quality data pipelines

Requirements

Expertise in working with large healthcare datasets (eligibility, medical / pharmacy claims, prior auth, ADT, etc.), ideally in a healthcare-focused technology startup with mature data structures and pipelines.
Experience designing data models to support both operations and analytics and building the data transformations in SQL to bring them to life.
An ability to “see beyond the question” to develop scalable solutions that are easily learned and reused by internal customers.
Experience with, or willingness to quickly learn, dbt and Looker.

Nice To Haves

Worked with large datasets, ideally in a healthcare-focused technology startup with mature data structures and pipelines as an Analytics Engineer, Data Scientist, or Data Engineer.
Proficiency in data modeling, transformation, and claims analytics is crucial.
Familiarity with dbt is preferred, but we are open to candidates willing to learn it quickly.
A working knowledge of Python and experience with Looker or similar BI tools for data analysis and visualization is a plus.
Clear communication. You can effectively convey your thoughts and ideas to both technical and non-technical colleagues and stakeholders.
Comfort with ambiguity. You have a successful track record working at scaling organizations, in fast-paced environments, and at ambitious startups. You navigate through challenges and find solutions in uncertain situations.

Responsibilities

Collaborate closely with our Product Manager and our Growth and Operations teams to understand, ingest, and accurately model healthcare data for new and existing customers, supporting updates and fixes throughout the life of the relationship.
Develop novel attributes and flags from our existing data to drive action on our Care Team, and build visualizations to report on their impact.
Gain a deep understanding of our data platform and contribute to improving our data models and pipelines using SQL and dbt.
Collaborate with other data scientists, data engineers, and analysts to build scalable and sustainable data models and pipelines.
Transform incoming eligibility, claims, prior auth, and ADT data to fit into our standard data models, identifying data quality issue or proposed standard data model enhancements as needed.
Translate business requirements into technical plans so you can design data models, pipelines, and analytics before you begin building them.
Build relationships with data teams at risk-bearing entities (insurers, ACOs, PCPs, etc.) and demonstrate Thyme Care’s expertise in building data & analytics products.
Ensure that internal customers have fast, accurate, and reliable access to data, supporting their decision-making and operations with high-quality data pipelines.