Rachael is a data science and machine learning engineer with 5 years of experience developing and optimizing automated, data driven tools – from interactive executive dashboards, to free, open source AI applications. Skilled in business translation, python, and cloud based platforms with a focus on responsible and user friendly solutions. Adept at transforming complex business challenges into production-ready products through CI/CD and close cross-functional collaboration. Passionate about advancing equitable technology that improves decision-making and saves users time.
Masters in Applied Data Science (AI Focus)
Univesity of Chicago
Bachelors of Arts
University of Washington
My goal is to harness data science and AI to create tools that simplify complex workflows and empower informed decision-making. I aim to turn data into actionable insights that help teams work more efficiently and strategically. Ultimately, I strive to make advanced analytics accessible and impactful across both technical and business domains.
Please reach out to collaborate 😃
ABSTRACT Introduction/Aims Claims-based analyses have demonstrated high medical costs associated with myasthenia gravis (MG). We examined the economic burden of MG from the …
This manuscript provides a description of MOVR, participants enrolled in MOVR, and longitudinal data availability.
Introduction Business at Maxim Integrated is focused on solving engineering problems to empower design innovation and create products that shape the world. One such application of …
