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Stanford Health Care seeks a Lead Data Engineer to join a team building AI-enabled health care solutions across patient care, research and administration. You will design, scale, and maintain compute frameworks, tooling, and model implementations used by the data science team.
You’ll collaborate with clinical and operations staff to deploy algorithms that improve outcomes, reports to the Data Science Director, and help ensure robust data processing software and infrastructure across SHC’s health
If you're ready to be part of our legacy of hope and innovation, we encourage you to take the first step and explore our current job openings. Your best is waiting to be discovered.
Day - 08 Hour (United States of America)
The Lead Data Engineer will be part of a team building Stanford Health Care's (SHC) solutions incorporating Artificial Intelligence including providing health care solutions in the areas of patient care, medical research and administrative services. This group is designed to bring Artificial Intelligence (AI) and other emerging machine learning (ML) based innovations in data science into healthcare and will partner closely with individuals across clinical specialties and operations areas to deploy algorithms that can lead to better patient outcomes. Reporting to the Data Science Director and working closely with Stanford Medicine's inaugural Chief Data Scientist, this role will be responsible for building, scaling and maintaining the compute frameworks, analysis tooling, model implementations and agentic solutions that form our core AI platform.
This is a Stanford Health Care job.
The Lead Data Engineer will be part of a team building Stanford Health Care's (SHC) solutions incorporating Artificial Intelligence including providing health care solutions in the areas of patient care, medical research and administrative services. This group is designed to bring Artificial Intelligence (AI), predictive algorithms and other emerging machine learning (ML) based innovations in data science into healthcare and will partner closely with individuals across clinical specialties and operations areas to deploy algorithms that can lead to better patient outcomes. Reporting to the Data Science Director and working closely with Stanford Medicine's inaugural Chief Data Scientist, this role will be responsible for maintaining compute frameworks, analysis tooling, and/or model implementations used or created by the team. The individual will design, implement, and support data processing software and infrastructure.
Stanford Health Care
Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford's patient-experience and represents a framework for patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery.
Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements.
Base Pay Scale: Generally starting at $97.18 - $128.78 per hour
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.