Data Scientist / Data Engineer

80 Beats Medical is a Berlin-based medical technology company developing innovative solutions for cardiovascular and vascular diagnostics. Our VICORDER® platform enables non-invasive assessment of vascular health Building on this established technology, we are expanding our clinical diagnostic portfolio by combining medical device technology with advanced data analytics and AI. Our goal is to transform complex physiological and cardiovascular data into reliable, clinically meaningful insights that can support earlier risk detection and better-informed clinical decisions. We are a growing, international team working at the intersection of medical devices, software, data science, and clinical research. We are looking for an experienced Data Scientist / Data Engineer to help build the data and AI infrastructure behind our next generation of medical diagnostic solutions. You will work with high-frequency physiological and clinical data, developing secure and scalable data pipelines and supporting the transition of machine learning models from research into production-ready clinical applications. You will work closely with our software, clinical, and regulatory teams in a highly interdisciplinary environment. Tasks Design, build, and maintain robust, scalable, and secure data ingestion and transformation pipelines. Implement automated ingestion, validation, lineage tracking, and quality monitoring. Develop and maintain reusable data libraries, transformation logic, and governance frameworks. Ensure full compliance with GDPR, NIS2, Cyber Resilience Act (EU), HIPAA (US) and other global regulatory frameworks. Experience with implementation of Role-based access control (RBAC), Encryption in transit and at rest (HSM/KMS), Data anonymization & pseudonymization workflows and Consent handling and audit mechanisms. Participate in security audits, compliance reviews, and certification efforts. Operationalize AI pipelines including model deployment, monitoring, drift handling, versioning, and automated retraining. Deploy explainable AI tooling (SHAP/LIME) into the pipeline for auditability and compliance. Maintain CI/CD workflows for data and ML workloads. Develop Python-based analytics scripts, reusable data modules, and feature engineering logic. Support visualization of workflows. Ensure reproducibility and model traceability across the full lifecycle. Requirements QUALIFICATIONS Degree in Computer Science, Engineering, Data science, AI, Cybersecurity, or similar. 5+ years of experience building secure, compliant cloud-based data ecosystems ( for regulated data domains. Hands-on experience with time-series data, sensor data, or biomedical/wearable data. Knowledge of statistical programming Strong understanding of ML approaches for classification, anomaly detection, and prediction using high-frequency data. Proficiency in one or more programming languages Advanced experience with Orchestration, Data frameworks, and Infrastructure automation. Proven cross