Seattle, Washington, United States
Building business intelligence systems that scale and deliver, with cross-industry depth across healthcare and pharmaceutical analytics. Passionate about hard problems at the intersection of data, AI, and clinical operations. If you are working on interesting problems in analytics, AI, or data, let's connect!
-Developed end-to-end business intelligence infrastructure for a Fortune 500 enterprise, processing 400K+ SAP transactions to design automated data pipelines and decision support tools projected to deliver $150K–$300K in annual cost savings. -Built and owned a scalable quarterly reporting framework integrating multiple enterprise data sources, enabling continuous performance monitoring and data-driven decision making for operations leadership. -Developed a production-grade AI analytics agent using Retrieval Augmented Generation (RAG), enabling natural language querying of live enterprise data and reducing time-to-insight from 20 minutes to seconds.
-Developed and maintained reporting pipelines and data workflows across multiple clinical data sources, ensuring data accuracy and compliance for 500+ pharmaceutical drug candidates across clients including Pfizer, GSK, and Merck. -Designed and delivered 12+ executive dashboards in Power BI and Tableau tracking clinical portfolio KPIs and compound progression milestones, adopted as the primary self-service analytical view for 50+ stakeholders including senior leadership. -Engineered automated reporting pipelines in Python, R, Power Query, and DAX, eliminating ad-hoc analysis workflows and standardizing data flows across multi-disciplinary research teams, supporting $2M+ in regulatory submissions
-Built data pipelines to consolidate field data from global pilot programs across multiple regions, ensuring data integrity and consistency for reporting. -Wrote analytical reports and visualizations to communicate program performance to grant stakeholders and organizational leadership. -Contributed to program evaluation frameworks, translating raw operational data into measurable outcomes for decision-making.
-Analyzed ChIP-chip epigenetics datasets to identify chromatin occupancy patterns across multi-variable experimental conditions, maintaining data integrity and accuracy throughout the research pipeline. -Produced structured analytical reports translating complex experimental findings into clear summaries supporting faculty research and academic publication workflows. -Collaborated with faculty researchers to design data collection protocols and document research outcomes across experimental cycles.