Sbc Sr Data & Ai Solutions Eng

1.0 FTE Full time Day - 08 Hour R2660734  SBC Business Intelligence Allied Health PALO ALTO, 3373 Hillview Ave, California

Day - 08 Hour (United States of America)

The SBC Sr Data & AI Solutions Engineer designs Artificial Intelligence (AI), predictive algorithms and other emerging machine learning (ML) innovations and integrates into SBC operations to improve outcomes, drive resource optimization and help meet blood transfusion and transplantation requirements. This role also leads end-to-end Extract Transformations and Load (ETL) pipelines to unify data across databases, data marts, and the EDW;

enhances BI capabilities to drive data-driven decisions, optimize blood production and testing workflows, and monitor performance with proactive support.

Stanford Blood Center

• Applies solid software development and object-oriented programming (OOP) skills to build applications and front-end web solutions.
• Builds, deploys, and maintains AI and ML solutions across clinical, laboratory, and operational domains to improve outcomes while upholding safety, ethical governance and cost-effectiveness
• Utilizes Python data science capabilities and leverages libraries (virtual environments, REST APIs) to accelerate analytics delivery, solve complex problems efficiently, and build scalable data pipelines and applications, ensuring reliable technical support and timely troubleshooting.
• Leverages deep expertise in large language models (LLMs) and smaller language models (SLMs) to fine-tune, engineer prompts, and deploy AI solutions that enhance business analytics, product development, data-driven decision making to help boost productivity.
• Develops/enhances BI and ETL processes that reflect best practices for error handling, operations logging and alerting, scheduling, and job control. Prepares specifications, designs, data models and diagrams from which databases can be developed and manages a common data model to harmonize relational databases, tune queries to optimize the EDW and BI architecture while monitoring performance with proactive support.
• Applies advanced data analysis, forecasting, predictions and simulation methods to project demand for services and blood products, driving supply chain optimization and optimal resource allocation.
• Identifies improvements to operational processes including productivity analysis, process engineering and optimization and leads projects to implement such improvements applying solid project management skills, team/user communications, etc.
• Assumes broader responsibilities to meet evolving business needs and uphold department efficiency, while mentoring BI analysts to grow their capabilities
• Complies with governmental regulations and Stanford Health Care and Blood Center policies regarding health and safety. Observes and supports good health and safety practices.
• Strictly observes privacy and security related policies, procedures and practices to preserve the integrity and confidentiality of medical and other sensitive information pertaining to donors, patients, research subjects, and team members. Acts as a responsible information steward and treat information as sensitive and confidential in accordance with federal and state laws and with professional ethics, accreditation standards and legal requirements. Do not disclose protected health information inappropriately.
• May be required to enter areas where other individuals work with human blood; potential may exist for unanticipated exposure to blood borne pathogens by splash or spill.

• Bachelor's Degree in engineering, computer science, data science or related field plus 4 years of experience with applied problems required
• Master's Degree in engineering, computer science, data science or related field preferred

• 3+ years to 5 years hands-on experience designing and developing software (across the full lifecycle), AI, and BI solutions; accountable for a complex EDW environment, driving performance with robust ETL processes required

• Experience developing, evaluating, and implementing Machine Learning and Artificial Intelligence models while partnering with individuals across clinical and operational areas to deploy algorithms and solutions that can lead to better outcomes and optimization of resources while validating both researcher-built and vendor-provided algorithms or AI solutions
• Advanced OOP-based…