Application Scientist - Digital Pathology

Position Summary

We are seeking an Application Scientist to serve as the technical bridge between product, engineering, data science, laboratory operations, and clinical stakeholders in digital pathology. You will own the end to end technical readiness of whole slide image based solutions—from image calibration and image lifecycle management to clinical grade algorithm deployment. This role emphasizes imaging science, data analytics, and validation over pure software engineering, ensuring our solutions meet clinical quality, performance, and regulatory expectations.

The ideal candidate combines hands on lab/WSI experience with strong systems thinking, excellent stakeholder communication, and a bias toward operational reliability and regulatory compliance.

• Administer and optimize IMS workflows (user provisioning, access control, retention, tiered storage, audit trails).
• Investigate incidents and lead corrective actions to improve stability and user experience.
• Define and enforce metadata and ontology standards (specimen, stain, region annotations, versioning) and file format policies (SVS, SCN, NDPI, TIFF/OME TIFF).
• Collaborate with cloud team to implement data monitoring and data governance (PII/PHI safeguards, de identification, consent tracking).
• Build operational runbooks for ingestion, migration, archival, and disaster recovery.

• Design, execute, and document calibration protocols for brightfield/fluorescence WSI scanners (color calibration, focus metrics, illumination uniformity, ICC profiles).
• Implement/validate color management pipelines to reduce site to site variability.
• Build and maintain image QA dashboards (PSNR, SSIM, CIEDE
  2000, artifact scoring, blur detection, tissue coverage).
• Collaborate with scanning operations and vendors to troubleshoot imaging issues (scanner drift, compression artifacts, barcode/label problems) and drive root cause analysis.

• Productionize and maintain AI/ML pathology algorithms (detection, grading, quantification, triage) with attention to performance, reproducibility, scaling and monitoring.
• Package models with Docker and orchestrate via AWS; implement CI/CD for model and pipeline updates.
• Collaborate with data science and external collaborators to translate research models into deployable services, including GPU resource planning and batch/stream inference.
• Establish real time/near real time inference pathways, results persistence, and human in the loop review tools.
• Define and track validation metrics (accuracy, sensitivity/specificity, AUC, turnaround time, uptime).

• Author and maintain SOPs, validation plans, and technical files; support CAP/CLIA readiness for regulated use.
• Maintain software quality by performing UAT, bug tracking and reporting.
• Perform risk assessments (cybersecurity, model drift, data integrity) and drive corrective/preventive actions (CAPA) in collaboration with Quality teams.
• Conduct training and change management for pathologists, lab personnel, and IT.

• Serve as subject matter expert for proof of concepts and end-user onboarding for digital pathology solutions.
• Translate clinical/operational needs into requirements for product and engineering; manage pilots and rollouts with clear success criteria.
• Provide tier 2/3 support for imaging and algorithmic workflows and create knowledge base content.
• Responsible for technical integrity of project deliverables, including quality and compliance to applicable standards.
• Fosters a data-driven, evidence-based mindset and reporting format across the digital pathology team.
• Provides technical direction and accountability for our expanding digital pathology portfolio by driving leading-edge thinking and state-of-the-art technology into processes and products.
• Other duties as assigned by the leadership.

• PhD in Biomedical Engineering, Computer Science, Medical Physics, or related field; or equivalent experience.
• 5+ years in digital pathology or medical imaging (WSI scanners, histology workflows, image QC).
• Demonstrable experience with image calibration and color management (ICC, white balance, shading correction) and stain normalization.
• Hands on with IMS and DICOM/HL7/FHIR integrations; familiarity with LIS/LIMS.
• Proven track record of algorithm deployment (Docker/Kubernetes, CI/CD, GPU acceleration) and MLOps (model packaging, monitoring, rollback).
• Proficiency in Python (Num Py, OpenCV, scikit image, PyTorch/Tensor Flow), image formats (SVS, NDPI, DICOM, OME TIFF), and annotation tools (QuPath, Slide Viewer, PathML).
• Experience with UI/UX feedback in viewer tools (annotation, ROI selection, overlay management) and pathologist workflow optimization.
• Strong documentation skills and experience writing SOPs/validation reports for regulated environments.
• Excellent communication and stakeholder management; able to…