Data Scientist / Biostatistician (all genders) - AF-B-STEP

Data Scientist / Biostatistician (all genders) - AF-B-STEP

Bookmark jobad Share jobad

Job-ID: J000006331

Contract Type: Temporary

Employment Type: Full time/ Part time

Closing Date: 11.05.2026

Organization: UKE_Herz- und Gefäßzentrum

Category: Research & Science

Department: Klinik für Kardiologie

Main tasks

At the University Heart and Vascular Centre (UHZ) of the University Medical Center Hamburg-Eppendorf (UKE), we redefine cardiovascular research by embedding large-scale clinical and translational science directly into our everyday clinical care. Our ecosystem combines deeply phenotyped cohort studies with more than 10,000 participants, comprehensive biobanking, longitudinal follow-up, and patient-centred research enabled by remote monitoring and connected wearables. We lead and contribute to multinational trials that shape clinical guidelines.

AF-B-STEP is a newly launched EU-IHI consortium co-ordinated by our centre. It tackles one of the most consequential open questions in arrhythmia research: how atrial fibrillation burden should inform diagnosis, risk stratification, and treatment – with direct relevance for FDA and EMA regulatory decisions. The consortium unites 18 partners from academia, industry, and patient organisations across Europe and Canada, integrating data from 60+ clinical trials and 500,000 patients. More at afburden.org.

Your role. You architect and operate the data backbone of the consortium, and lead analyses from one of the largest harmonised cardiovascular datasets: AF-BOLD, combining 200,000+ patient-years of AF burden and health outcome data from 60+ trials. You design and implement pipelines for semi-automated harmonisation, quality assurance, and AI-driven anomaly detection across heterogeneous clinical data sources – structured records, cardiac device remote-monitoring data, digital ECGs, wearable time series, and insurance claims – into a unified, FAIR-compliant resource. You coordinate the core data science team across the consortium, support mentoring junior researchers, and develop modern metadata management strategies with semantic enrichment (SNOMED CT, LOINC) and AI-supported extraction from clinical documents. You work directly with data owners from leading academic institutions and industry partners, publish findings relevant for both clinical practice guidelines in the field and regulatory decisions of governing agencies in top-tier journals, and shape research that informs treatment decisions across the globe.

This position is a full-time (100% of the regular weekly working hours) fixed-term position for an initial period of three years due to third-party funding. An extension is anticipated. Part-time work may be possible.

Your Profile

Masters degree or PhD in Data Science, (Bio)Informatics, (Bio)Statistics, or a closely related quantitative field

Minimum of two years of post-graduate professional experience, clearly documented in your CV (student jobs, working student positions, and internships do not qualify)

Technical excellence in Data Science and Data Engineering, demonstrated through an active GitHub profile, peer-reviewed publications, or a comparable project portfolio

Proficiency in PyTorch, combined with hands-on experience in developing modern microservice- and API-based software while adhering to high software quality standards

Solid experience working with relational databases (e.g., PostgreSQL), object storage (e.g., MinIO), and version control systems, including CI/CD pipelines with Git and GitLab

Genuine curiosity about clinical cardiovascular medicine, intrinsic motivation, and a highly results-oriented mindset, and you should possess strong self-management skills. You can articulate and demonstrate all of these in your cover letter and interview