Jobs at Prolaio

Design and govern Prolaio's regulated healthcare data platform: define architectures, models, pipelines, and lifecycle management for clinical, device, claims, and patient-generated data; apply healthcare terminologies and common data models; enable secure, interoperable, AI-ready datasets for analytics, research, clinical operations, and regulated workflows.

The Lead Software Quality Engineering, Backend will oversee validation of a cloud-based data platform, lead a team of engineers, and contribute to automation and verification strategies for healthcare technologies.

As a Data Science Intern, you will develop and validate LLM pipelines for extracting clinical endpoints from EHR data, ensuring data quality for clinical analysis.

Serve as primary client contact for clinical research projects; lead internal teams to deliver projects on time and budget; onboard and train clients; identify growth opportunities; support contracting, pricing and budgets; generate performance reports; resolve operational issues and drive continuous improvement to grow accounts and ensure excellent client service.

Design, build, and maintain scalable backend integration services (Kotlin/Python) connecting healthcare systems, ERPs, and analytics. Own API design, cloud/container deployments (GCP, Docker/K8s), data pipelines into BigQuery/Dagster, monitoring/alerting, and security/compliance (HIPAA, SOC2). Mentor junior engineers and collaborate cross-functionally to ensure reliable, secure data flows.

Lead definition, roadmap, and validation of clinical endpoints for cardiovascular trials, including digital biomarkers, sensor and lab-based measures, and ePRO/eCOA. Select sensors/partners, define raw data capture, work with Data Science and Clinical on biomarker development, ensure regulatory and quality readiness (FDA/EMA, validation frameworks), and engage sponsors to prioritize and deliver trial-ready measures.

The Senior Data Scientist will develop risk prediction models and perform statistical analyses on clinical datasets, focusing on digital biomarkers for cardiovascular disease. Responsibilities include data pipeline development, cross-team collaboration, and scientific publications.

Support production quality activities including supplier qualification, in-process and finished goods inspections and release, environmental monitoring, complaint investigations, and transfer of products/processes from Design to Production. Report quality metrics to management and support regulatory compliance (ISO 13485, CFR Part 820).