Principal Data Scientist - Surgical AI

KaashTech LLC

Santa Clara, CA, United States

2 days ago

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Role details

Contract type

Contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Computer Vision Audit Trail Machine Learning Azure Machine Learning Software Deployment Data Processing Feature Engineering Model Validation Meditech Software Version Control

+2 more

Data Pipelines Databricks

Job description

Lead model design and experimentation strategy for surgical AI systems, defining architecture decisions, feature engineering approaches, and validation methodologies based on clinical context and site-specific constraints.
Conduct on-site hospital workshops with clinical stakeholders to establish project scope, identify technical constraints, define success metrics, and translate clinical requirements into data science objectives.
Partner directly with clinicians throughout the model development lifecycle, ensuring surgical expertise informs every decision from data collection through final evaluation and deployment.
Own end-to-end model development and validation, including data curation, feature engineering, model training, performance evaluation, and comprehensive documentation with full lineage tracking and model cards.
Design for real-world variability across hospital sites, accounting for differences in data quality, procedure coverage, annotation consistency, surgical equipment (robotic-assisted vs. laparoscopic), and clinical workflows.
Implement MedTech-grade validation protocols that maintain complete traceability of datasets, annotations, training runs, evaluation results, and deployed artifacts; serve as one of three required sign-offs before clinical deployment.
Collaborate with cross-functional pod teams-Data Engineers and ML Engineers-to build robust data pipelines, feature tables, training infrastructure, model versioning systems, and experiment tracking frameworks.
Transfer knowledge and IP fully to client organizations, ensuring hospitals own all models and intellectual property while building internal capability for ongoing model management and improvement.

Requirements

15-20 years of professional experience in data science, machine learning, or related fields
Demonstrated expertise in model design, experimentation, and evaluation through production deployment cycles
Hands-on experience with surgical AI, multimodal data (surgical video, EHR data, device telemetry), or similar healthcare applications
Proven ability to work within PHI and HIPAA compliance frameworks, including de-identified data handling
Proficiency with enterprise ML platforms (AWS SageMaker, Databricks, or equivalent)
Strong facilitation skills to conduct workshops with clinical stakeholders and translate clinical needs into technical scope
Ability and willingness to work onsite at hospital locations throughout the United States
Experience with model validation, regulatory documentation, and clinical-grade quality standards, * Background in clinical medicine, surgery, or healthcare operations
Experience with video analysis, computer vision, or temporal data modeling
Familiarity with FDA regulatory pathways or medical device validation processes
Prior work in regulated industries (MedTech, pharmaceuticals, etc.)
Experience with model governance, audit trails, and compliance documentation
Knowledge of surgical workflow optimization or OR analytics

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