Senior Data Scientist

Karoo Health

21d

About The Position

Karoo Health is seeking a Senior Data Scientist to join its Engineering team and help build the data systems behind its platform for improving cardiovascular care and supporting value-based care. The role offers an opportunity to shape the technical solution at an early-stage, venture-backed healthcare startup. Pittsburgh is preferred, but U.S.-based remote work is possible. The Senior Data Scientist will lead the design and development of reliable, scalable, and secure data architecture; create foundational healthcare data models and schemas; and build production-grade pipelines that ingest, process, enrich, and normalize healthcare data. The role also encompasses data quality and governance, system performance optimization, cloud infrastructure, healthcare data security and regulatory compliance, and direct, bidirectional integrations with electronic medical record platforms. The position calls for deep healthcare data expertise, including familiarity with common data standards and models, as well as substantial experience in data science or data engineering. The successful candidate will make high-impact technical decisions independently and work collaboratively to develop high-quality solutions to complex problems. Applicants are asked to include a description of their interest in the role. Candidates must be legally authorized to work in the United States without current or future employer sponsorship.

Requirements

Deep, hands-on experience with healthcare data, including standards and common data models such as TUVA, OMOP, or FHIR.
Demonstrated experience designing core data models and schemas from scratch and translating business, clinical, product, or user requirements into scalable data structures.
Experience mapping raw healthcare data into standardized models and resolving data quality, normalization, terminology, and structural inconsistencies.
Hands-on experience integrating directly with EMR/EHR platforms; experience with eClinicalWorks, AthenaOne, Epic, or comparable systems is preferred.
Experience with healthcare data regulations such as HIPAA and HITRUST and data formats such as FHIR.
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent work experience.
At least 8 years of dedicated professional experience in a Data Scientist or Data Engineering role; startup or fast-paced healthcare technology experience is preferred.
Expert proficiency in SQL and at least one data-processing programming language, such as Python or Scala.
Deep experience designing and managing data warehouses such as Snowflake, Google BigQuery, or AWS Redshift, and experience with data lake technologies such as S3 or Delta Lake.
Hands-on experience with big data processing frameworks such as Apache Spark or Dask.
Deep understanding of cloud platforms, AWS preferred, and cloud-native development, including services such as S3, Lambda, and RDS.
Hands-on experience with workflow orchestration tools such as Apache Airflow or AWS Step Functions.
Expert knowledge of system architecture, scalability, and data-system performance optimization.
Experience with test automation, CI/CD, and DevOps best practices for data deployments.
Ability to work independently and make high-impact technical decisions.
Must be legally authorized to work in the United States and not require employer sponsorship now or in the future.

Nice To Haves

Experience in a startup or fast-paced healthcare technology environment.
Experience integrating with eClinicalWorks, AthenaOne, Epic, or comparable EMR/EHR systems.
Experience with AWS is preferred.

Responsibilities

Lead the design, construction, installation, and optimization of reliable, scalable, and secure data architecture.
Design and evolve foundational healthcare data models and schemas, using standards such as TUVA, OMOP, and FHIR to translate clinical, operational, product, and reporting needs into scalable structures.
Build and maintain production-grade pipelines that ingest, process, enrich, and normalize healthcare data while ensuring consistency, usability, and integrity.
Establish and enforce data quality standards, monitoring, and validation processes.
Optimize data processing and retrieval through query tuning, indexing, and partitioning strategies.
Design and deploy scalable, secure cloud infrastructure using infrastructure-as-code best practices.
Ensure compliance with healthcare data regulations, including HIPAA and HITRUST, and implement data security best practices.
Develop direct, bidirectional integrations with electronic medical record platforms.