Clinical Data Management Specialist

We are DeepHealth, a global leader in providing AI-powered health informatics for real-world clinical settings and screening programs that aim to empower breakthroughs in care delivery.

DeepHealth, a wholly owned subsidiary of RadNet, Inc., has an integrated portfolio that addresses challenges across the entire radiology value chain—from referral management, scheduling, and patient engagement to technologist and radiologist workflow—and leverages advanced AI to improve operational efficiency, clinical confidence, and patient outcomes.

Responsibilities

The role will be responsible for ensuring the availability, quality, and integrity of clinical data used for AI development and validation. You will play a central role in curating, processing, and managing medical imaging datasets that directly impact the performance, clinical evaluation and safety of our products.

What kind of work we expect from you:

· Align with stakeholders (product management, clinical science, and ML teams) to select appropriate cases for training and validation of ML models.

· Manage the end-to-end data collection and annotation pipeline, including coordinating annotation workforces, uploading and organizing data, and ensuring accuracy of outputs.

· Perform quality assurance on datasets and annotations, ensuring compliance with regulatory and scientific standards.

· Organize and integrate diverse data sources, converting between formats (DICOM, PACS, Nifti, etc.) and maintaining data consistency and reliability.

· Build and optimize pipelines and tools for dataset management, validation, and analytics.

· Use SQL and BigQuery to query, manage, and analyze large-scale datasets.

· Ensure data management platforms and validation datasets adhere to regulatory guidelines (e.g. FDA submissions).

· Collaborate with the team to make strategic recommendations and improvements to data workflows.

What we value

· Strong analytical mindset and attention to detail.

· Ability to communicate complex topics effectively to a range of technical and non-technical stakeholders.

· Not afraid of working inside a strong regulatory framework and disciplined about rigorous data quality needs.

· Ability to balance efficiency with accuracy, understanding when to prioritize speed and when to enforce deeper quality checks.

· Ability to take ownership of complex processes and deliver results collaboratively.

Required Experience

· 3 years of experience curating and managing large datasets.

· Experience working with medical data (PHI), anonymization, and labeling.

· Strong programming skills in Python and its scientific computing libraries (pandas, numpy, etc.).

· Hands-on experience with medical imaging formats and tools (DICOM, PACS, Nifti, pydicom, SimpleITK).

· Experience with at least one annotation platform (e.g. RedBrick, 3D Slicer, ITK-SNAP).

· Experience with cloud platforms (GCP or AWS) and strong skills in SQL and BigQuery.

· Fluent in English.

Nice to have

· Experience in the MedTech field.

· Familiarity with R.

· Experience developing analytics or visualization tools for large medical datasets.

What we offer

· A chance to have a real impact on the fight against cancer. · Hybrid position, based in The Netherlands.

· 25 vacation days (on a full-time basis plus local legal holidays).

· A modern technology stack: Google Cloud Platform with a strong preference for cloud-native and serverless deployment.

· Lots of autonomy, lots of responsibility.

· Very smart, passionate colleagues