Rachael is a data science and machine learning engineer with 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.
Outside of her professional life, Rachael enjoys living an active lifestyle full of weight lifting and outdoor sports, playing games with her friends (anything from board games to mobile games), volunteering with animal and environmental welfare organizations, reading and cooking.
Masters in Applied Data Science (AI Focus)
University of Chicago
Bachelors of Arts
University of Washington
I’m passionate about using data science and AI to create tools that simplify complex workflows and empower informed decision-making. I love turning 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 Claims-based analyses have demonstrated high medical costs associated with myasthenia gravis (MG). We examined the economic burden of MG from the perspective of affected …
This manuscript provides a description of MOVR, participants enrolled in MOVR, and longitudinal data availability.
Abstract Demand for portable computers, known as edge computing devices, has been on the rise in the past decade. To keep pace with the ever increasing speed of the internet, …
