Staff Biomedical Data Manager
About The Position
PathAI is hiring a Staff Biomedical Data Manager to lead biomedical data architecture, management, governance, and quality for large-scale, multimodal clinical programs, including whole slide imaging. The role partners with leadership in machine learning, biomedical data science, program management, Algorithm Product, and Translational Research to define how clinical and translational research datasets are governed, structured, and scaled. The manager owns the vision for maximizing the company platform’s capabilities and drives its technical roadmap and scalable process architecture. As the primary technical authority for the digital pathology data domain, this position works with partners on complex integrations and establishes data standards and best practices across products and partnerships. It leads the design of reusable data models and workflows, serves as a subject matter expert on clinical data digitalization, and provides technical guidance on complex machine-learning platform deployment, validation, and data integration challenges. The role also oversees and automates algorithm deployment and lifecycle management, develops tools to improve data quality and delivery speed, defines team tooling strategy, and governs technical documentation, SOPs, and cross-functional training. The position is based at the Boston, Massachusetts office. Telecommuting from a home office may also be allowed. Multiple positions are available.
Requirements
- Bachelor’s degree in Biomedical Informatics, Biomedical Engineering, Public Health, Epidemiology, Biostatistics, or a related field, plus three years of experience as a Staff Biomedical Data Manager or progressive experience in biomedical data management focused on data architecture, curation, and communication; experience may be gained concurrently.
- Alternatively, a master’s degree and two years of experience.
- Two years of experience using Python or R for large-scale data wrangling, statistical modeling, and automated reporting.
- Two years of experience architecting and maintaining production-grade ETL/ELT pipelines using industry-standard tools such as Spark, Airflow, or Databricks, or similar.
- Two years of experience managing datasets within strict regulatory frameworks.
- Two years of experience with data harmonization and standardization, including mapping disparate data sources to common data models.
- One year of experience managing end-to-end digital pathology workflows, including ingestion, storage, and metadata extraction for whole slide images (WSI).
- One year of experience utilizing CI/CD for data (GitHub Actions), data monitoring and observability tools, and environment management (Docker).
- One year of experience working with medical terminology in oncology and pathology or clinical trial structure.
- One year of experience working with oncology-specific data archetypes, including TNM staging, histology codes, and biomarker status.
- One year of experience working with sensitive datasets.
Responsibilities
- Partner with leadership in machine learning, biomedical data science, and program management to define governance, structure, and scaling for clinical and translational research datasets.
- Own the vision for maximizing platform capabilities and architect improvements for hosting high-velocity, multimodal histopathology data.
- Serve as the primary technical authority for digital pathology data and interface with partners on complex integrations.
- Architect and own end-to-end data management, governance, and quality strategy for large-scale multimodal clinical programs, including whole slide imaging.
- Drive the technical roadmap for data platform evolution in partnership with senior leadership.
- Establish technical standards and best practices for data management processes across products and partnerships.
- Translate partner needs for clinical data digitalization into scalable technical requirements for platform teams.
- Lead the design and implementation of scalable, reusable data models and workflows for novel projects.
- Design robust solutions for complex deployment, validation, and data integration challenges on internal ML platforms.
- Oversee and automate execution, validation, and lifecycle management of major algorithm deployments, maintaining data integrity from ingestion through analysis.
- Develop solutions and tooling to abstract data workflows, improve data quality, and reduce time to delivery.
- Define long-term team tooling and efficiency strategy, and identify, vet, and champion new technologies.
- Provide technical leadership and guidance on complex data-related barriers.
- Create and govern standards for technical documentation, SOPs, and cross-functional training.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
