Data Scientist / Data Engineer

Nucs AI · Berlin, Berlin, Germanymid

En corto

▸Construir y mantener pipelines de datos auditables para imágenes médicas y datos clínicos en la nube.
▸Analizar datos clínicos y de diagnóstico con ML clásico, deep learning y LLMs, enfocándose en calidad y reproducibilidad.
▸Trabajar en un entorno médico de alto impacto con regulaciones estrictas, desde el inicio de una startup en crecimiento.

Working fluency with English

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

¿Qué piden?

✓3+ años de experiencia en ciencia de datos, ingeniería de datos, IA médica o campo relacionado.
✓Profundidad estadística aplicada a datos clínicos complejos y desordenados.
✓Experiencia comprobada en construcción y mantenimiento de pipelines de datos a gran escala.
✓Familiaridad con formatos de imágenes médicas (DICOM, NIfTI).
✓Experiencia práctica con ML clásico, ML explicativo y deep learning.
✓Conocimiento de buenas prácticas de software y gestión de línea de datos (proveniencia, trazabilidad).

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

GCPDICOMNIfTIMLDeep LearningLLMData PipelinesStatistical AnalysisModel EvaluationData Observability

¿A quién escribirle en Nucs AI?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

About Nucs AI Nucs AI is revolutionizing cancer care through cutting-edge AI and medical imaging technology. Founded in 2024 by a multidisciplinary team of oncologists, AI researchers, and healthcare innovators, we’re tackling one of medicine’s most pressing challenges: the growing demand for accurate, timely cancer diagnostics in the face of rising scan volumes and limited radiologist capacity. We sit at the intersection of diagnostics and treatment planning - building AI-powered tools at the convergence of medical imaging, radioligand therapy, and artificial intelligence. Starting with prostate cancer and expanding across oncology, we partner with world-leading medical institutions and pharmaceutical companies across the US, Europe, and Australia to bring precision oncology into everyday clinical practice. Our mission is to enhance diagnostic precision and expand access to expert-level cancer care, improving patient outcomes worldwide. We’re venture-backed, early-stage, and building a team that blends deep clinical expertise with engineering intensity - moving with the rigor the medical field demands and the speed the problem deserves. What you'll do Build auditable data pipelines for large clinical, diagnostic, and medical imaging datasets in the cloud. Own statistical analysis across clinical studies, diagnostic performance, model evaluation, and data quality. Apply classical machine learning and deep learning methods to data analysis problems. Use LLM-based methods to extract structured data from clinical documents and reports. Build dashboards and data observability tooling. Investigate and document missing, inconsistent, invalid, and implausible data. Maintain strong data lineage, provenance, traceability, and reproducibility across data workflows. Produce analyses and supporting evidence that hold up in regulatory submissions and audits. What we're looking for 3+ years of relevant full-time experience in data science, data engineering, medical AI, medical imaging, or a closely related field. Strong statistical depth applied to messy clinical or diagnostic data. A track record of building and maintaining data pipelines at scale. Comfort working with medical imaging formats including DICOM and NIfTI. Practical experience with classical machine learning and explainable ML. Working fluency with deep learning and modern LLM tooling. Experience with cloud data infrastructure. We use GCP, but equivalent platforms are fine. A strong working understanding of data lineage, provenance, traceability, and reproducibility. Unusual attention to detail around data completeness, validity, consistency, and edge cases. Flexibility at adapting to new technologies Awareness of good software practices Strongly preferred Experience with imaging-based clinical trials, preferably in nuclear medicine. Experience supporting FDA-cleared medical devices or EU MDR compliance. Experience producing statistical analyses or technical evidence used in a regulatory submission. Experience with DICOM de-identification and anonymization workflows. Experience with model interpretability techniques such as SHAP. Why Nucs AI Mission with real impact – Your work directly improves how cancer patients are diagnosed and treated. Ground-floor opportunity – Early-stage company, meaningful equity, and outsized influence on the direction we take. World-class collaborators – Work alongside leading oncologists, nuclear medicine physicians, and AI researchers globally. Massive market tailwinds – Radioligand therapy and AI-driven oncology are multi-billion dollar growth markets. Autonomy and flexibility – Remote-first, flexible working. We hire great people and trust them to deliver. Equity upside – Competitive equity package. We’re building something big and want you to share in it. How to Apply Submit your resume and a brief note on why this role and Nucs AI excite you. Equal Opportunity Nucs AI is an equal opportunity employer.

No apliques sin prepararte

Investigamos quién te entrevista, adaptamos tu CV y te ensayamos en vivo — gratis la primera.