Kansas City, Missouri, United States
Senior Database Administrator at the University of Iowa Healthcare with a Bachelor’s in Computer Science from the University of San Diego, bringing previous hands-on experience in machine learning and Workday integrations. Previously, as a Workday Integrations Consultant at Collaborative Solutions, I implemented client-centered solutions, optimized data flows, and supported seamless integration within the Workday ecosystem. Working across industries such as government and insurance, I configured EIBs and Core Connectors, enhancing operational efficiency and data insights. I also expanded my expertise in data science and AI, building on a strong foundation from a rigorous data science bootcamp with TripleTen and a machine learning engineer internship with Cuetessa, where I developed NLP models to analyze and classify emotional nuance in song lyrics. I later gained hands-on experience through internships at Celitech as an AI Product Engineer and at Colare as a Software Engineer, where I designed AI-driven chatbots, automation tools, and internal software solutions.
• Designed, built, and migrated reporting solutions from Tableau to Power BI for clinical and administrative departments. • Updated ETL workflows and reporting logic to modernize legacy processes and support the transition from the institution’s homegrown database to Epic’s Caboodle data warehouse, improving enterprise reporting reliability and data accuracy. • Streamlined legacy SSIS reporting workflows through Power BI automation, improving efficiency and maintainability.
• Guided enterprise AI customer support automation strategy by researching and evaluating 20+ AI tools for technical feasibility and commercial impact, helping leadership select reliable solutions and reducing manual support workload by 33%. • Streamlined decision-making and shaped the AI automation roadmap by preparing comparison matrices, reports, and presentations on AI tool capabilities and limitations, shortening decision cycles by ~50% and improving platform readiness.
• Identified $250K+ in new revenue opportunities by building an automated web-scraping system with TypeScript, BeautifulSoup, ChromeDriver, and DynamoDB to aggregate referral-bonus job listings across multiple third-party platforms. • Boosted recruitment efficiency by ~80% by building an OpenAI-powered batch resume upload feature, enabling multiple resumes to be parsed and processed simultaneously for each candidate, streamlining the overall recruitment workflow.
• Independently contributed to R&D efforts by building NLP models to analyze and classify emotional nuance in song lyrics. • Achieved a 40% improvement in classification accuracy by leveraging Python to design and train prototype NLP models (Logistic Regression, Random Forest, Naive Bayes, SVC, MLP, BERT). • Reduced model training time by 27% and improved overall processing performance by building an automated model-tuning and evaluation pipeline that integrated text preprocessing techniques such as tokenization, lemmatization, and TF-IDF. • Presented final project results to Cuetessa’s internal team, communicating model performance metrics, architecture and complex technical methods in an engaging way that helped inspire future product and research directions for the company.
• Delivered Workday integrations for 10+ clients across industries by leveraging ETL to configure and transform data, defining business requirements, leading design reviews with stakeholders, and implementing scalable solutions, cutting deployment timelines by ~25%. • Provided actionable and accurate data-driven insights and recommendations to both non-technical stakeholders and cross-functional teams, driving improvements in operational processes, project execution, and overall business outcomes. • Enhanced client adoption and operational efficiency by training 100+ users through live demos and creating technical documentation, enabling seamless go-live transitions and improving team productivity by ~75%.