Top Healthtech Data & Analytics Jobs

Cellanome is looking for passionate individuals to join their start-up team aimed at tackling significant challenges in biology. They offer diverse roles, emphasizing collaboration, innovative spirit, and career growth opportunities.

As a SAS Statistician, you will analyze Medicare claims data to drive insights for pharmaceutical companies, standardize processes, and train team members in SAS.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

As a Sr. Data Engineer at Lyra Health, you will build and scale core data infrastructure, design data warehouses, and create efficient data pipelines while collaborating across departments.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Design, build, and operate data services and pipelines to ingest, standardize, and deliver clinical data for product, analytics, and ML. Tune Spark workloads, enforce data quality, monitor production systems, and partner with product and engineering. Participate in on-call support.

The Research Data Manager oversees research datasets, quality assurance, compliance with HIPAA, and collaborates with clinical researchers to ensure effective data management.

As a Senior Data Analyst, you will analyze complex data, mentor junior analysts, develop AI-based tools, and ensure data integrity while collaborating with cross-functional teams to drive insights and strategic decisions.

Design, build, and maintain scalable batch and ELT/ETL data pipelines and services. Develop and operate Spark and Airflow workflows, apply software engineering practices, contribute to AWS-based systems, monitor and automate production, collaborate with product and data science teams, and mentor other engineers.

Build and maintain operations-focused dashboards and analyses to drive process improvement, quality, and efficiency. Integrate data from ADP, Smarteeva, and other sources; perform statistical analysis; present insights to leadership; partner with Technology and Process Engineering to support automation and monitor operational changes.