Jobs at Prolaio

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.

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.

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.

Develop and maintain mobile applications for Android, integrating medical device data, optimizing performance, and collaborating with backend teams and data scientists.

Lead product definition and delivery for AI, real-world data, and advanced analytics in cardiovascular research. Own strategy, discovery, requirements, prototyping, and agile delivery; partner with engineering, data science, clinical operations, and stakeholders to build AI-enabled dashboards, data products, and privacy-preserving analytics that improve trial execution and patient insights.

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.

Lead enterprise AI strategy and execution to design, pilot, deploy, and scale generative AI, conversational assistants, agentic automation, and AI-enabled workflows across clinical, product, and enterprise systems in a regulated healthcare environment. Align cross-functional teams, define success metrics, and ensure compliance, auditability, and continuous improvement of production AI capabilities.

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.

The Quality Specialist ensures quality control for production components and supplies, performs inspections, and manages complaint records in compliance with QMS.

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.