Design, implement, and maintain software systems and data pipelines supporting real‑world cancer genomics, medical imaging, and EHR data
Collaborate with interdisciplinary teams to translate analytical and research requirements into reliable, production-quality software
Develop tools and services for data ingestion, validation, transformation, storage, and access, ensuring performance and data integrity
Implement and carry out standard methodologies in software engineering, including version control, testing, documentation
Optimize systems for performance, scalability, and reliability across large and heterogeneous datasets
Communicate technical designs, trade-offs, and implementation details clearly to both technical and scientific collaborators
Contribute to open-source or internal software libraries, platform documentation, and long-term architectural planning

PhD in a computational science discipline required
Experience working with statistical and machine learning methods applied to genomics and/or imaging data
Experience in biotech, life sciences, or healthcare data environments
Familiarity with data storage and management systems, including SQL and NoSQL databases, object storage, data lakes, and data warehouses
Familiarity with common genomics and imaging data formats and standards (e.g., BAM, VCF, DICOM, OME‑TIFF)
Proficiency in one or more programming languages commonly used in data‑intensive systems (e.g., Python, R)

Bioinformatic Software Engineer III – Biostatistics Service

Key skills