SBC SR DATA & AI SOLUTIONS ENG

Tips: Provide a summary of the role, what success in the position looks like, and how this role fits into the organization overall. Responsibilities 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. 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 architecture and optimization for software and systems; proficient in Python (Django) and Java; HTML and CSS skills; experience with AI/ML deployment, including large language models (LLMs); proven performance tuning ability. End-to-end BI lifecycle ownership, including design, development, and deployment of BI solutions; BI tool administration; ETL design and development; EDW architecture; and delivery of robust reporting and analytics Extensive experience leveraging advanced analytics, forecasting, predictive modeling, and simulation to optimize operations; proven ability to communicate results to diverse stakeholders and management to drive engagement. Proficiency with BI and data visualization tools (i.e., Power BI, Tableau, SSRS, SAP BusinessObjects); SQL expertise in Oracle and MS SQL Server (Management Studio); SSIS; Azure DevOps Server; applying patches/upgrades; and monitoring hardware utilization for peak performance. Qualifications 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 #J-18808-Ljbffr Stanford Blood Center