This job has expired
This position was posted on November 28, 2025 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!
Job Overview
Location
1830 Embarcadero - PALO ALTO
Job Type
Full-time
Category
Data Science
Date Posted
November 28, 2025
Full Job Description
đź“‹ Description
- • Join Stanford Health Care’s elite Data Science team at the forefront of transforming medicine through Artificial Intelligence and Machine Learning. You will architect, train, and deploy predictive algorithms and agentic systems that directly improve patient outcomes, accelerate medical research, and streamline administrative workflows across one of the nation’s top academic medical centers.
- • Own the end-to-end lifecycle of AI/ML solutions—from problem framing with clinicians and researchers to scalable deployment in production cloud environments. You will translate complex clinical questions into tractable data science problems, curate multi-modal healthcare datasets (EHR, imaging, genomics, wearables), and engineer features that unlock new clinical insights.
- • Design and implement rigorous validation pipelines that ensure model safety, fairness, and clinical efficacy. You will conduct bias assessments, performance monitoring, and quality-control checks that exceed regulatory and ethical standards, safeguarding patient trust while advancing scientific discovery.
- • Collaborate daily with physicians, nurses, operational leaders, and Silicon Valley technology partners to co-create AI-enabled care pathways. You will translate model outputs into intuitive clinical decision tools, dashboards, and APIs that integrate seamlessly into Epic workflows and point-of-care devices.
- • Evaluate and select cutting-edge platforms (distributed cloud, GPU clusters, MLOps stacks) to accelerate experimentation and production deployment. You will champion best practices in reproducible research, version control, containerization, and continuous integration/continuous deployment (CI/CD) for healthcare-grade software.
- • Mentor junior data scientists and cross-functional analysts, fostering a culture of curiosity, statistical rigor, and ethical AI. You will lead internal workshops, publish in peer-reviewed journals, and present findings at national conferences, amplifying Stanford Health Care’s reputation as a global leader in AI-driven medicine.
- • Drive strategic data governance initiatives, ensuring HIPAA compliance and alignment with Stanford Medicine’s data security policies. You will partner with privacy officers and IRB committees to navigate complex regulatory landscapes while unlocking the full potential of real-world clinical data.
- • Continuously scan the horizon for emerging AI/ML breakthroughs—large language models, federated learning, causal inference—and pilot their application in oncology, cardiology, population health, and operational efficiency. Your innovations will directly reduce readmissions, personalize treatment plans, and optimize resource allocation.
- • Translate technical results into compelling narratives for executive leadership, securing funding and organizational buy-in for next-generation AI initiatives. You will quantify ROI through rigorous A/B testing and health-economic analyses, demonstrating measurable impact on quality metrics, cost savings, and patient satisfaction.
- • Champion Stanford’s C-I-CARE patient-experience framework by embedding empathy and human-centered design into every algorithm. You will ensure that AI solutions anticipate patient needs, simplify care coordination, and empower individuals to focus on healing and recovery.
🎯 Requirements
- • PhD or MS in Statistics, Biomedical Informatics, Computer Science, or related quantitative field; PhD preferred
- • 4+ years (MS) or commensurate experience applying ML/AI to real-world healthcare problems in clinical or research settings
- • Expert-level proficiency in Python, SQL, or R for large-scale data processing in distributed cloud environments (AWS, GCP, or Azure)
- • Demonstrated experience developing, validating, and deploying machine-learning models (supervised, unsupervised, deep learning, NLP) on electronic health record, imaging, or genomic datasets
- • Graduate-level knowledge of statistical inference, experimental design, and modern ML/AI techniques including transformers, causal inference, and bias mitigation
- • Excellent written and verbal communication skills with proven ability to translate complex analytics into actionable insights for clinicians, executives, and regulatory bodies
🏖️ Benefits
- • Highly competitive hourly base pay scale starting at $79.21–$104.97, with final rate determined by experience, education, specialty, and internal equity
- • Comprehensive health, dental, vision, and mental-wellness coverage for you and eligible dependents, plus generous PTO and paid holidays
- • Access to Stanford University courses, tuition reimbursement, and cutting-edge research collaborations that accelerate your professional growth
- • On-site fitness centers, commuter subsidies, and prime Palo Alto location at 1830 Embarcadero—steps from Caltrain and Silicon Valley innovation hubs
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Stanford Health Care
Stanford Health Care is an academic medical center operating as the adult hospital and clinics of Stanford Medicine, affiliated with Stanford University. It delivers tertiary and quaternary inpatient care, outpatient specialty services, and advanced procedures, integrating clinical practice with Stanford University School of Medicine research and education. Services span cancer, cardiovascular, neurosciences, organ transplantation, and surgical specialties. Facilities include Stanford Hospital and Hoover Pavilion in Palo Alto, California, serving regional and national patient populations while training medical professionals and conducting translational research.
Subscribe to the weekly newsletter for similar remote roles and curated hiring updates.
Newsletter
Weekly remote jobs and featured talent.
No spam. Only curated remote roles and product updates. You can unsubscribe anytime.
Similar Opportunities
2 months ago
Anyone AI Inc.
2 months ago
DICK'S Sporting Goods, Inc.
3 months ago
Carrier Global Corporation
2 months ago