I am a data scientist with 3 years of experience in data and am currently studying for a master’s degree in Data Science at Duke. I did my undergraduate studies in Computer Information Systems. Over the past few years, I’ve had the chance to work in various industries and areas within the data sphere.

I started my career as a Data Engineer at Digital Umbrella, where I built new data infrastructure, creating a data warehouse, designing ETL and ELT pipelines, developing custom components in Apache Airflow, and maintaining test and production systems to ensure data quality. This work helped me transfer my capabilities across different data areas, which inspired me to pursue my master’s degree in data science.

Between my first and second year of graduate school, I worked as a Data Science Intern at Siemens Healthineers. During this internship, I developed the model and infrastructure for customer churn prediction. The model achieved over 85 % accuracy and provided explanations for each decision through interpretability methods. All components were documented and deployed in a Streamlit dashboard for teams to use easily, and the module was built with extensibility in mind for future models.

During my academic career I’ve been a teaching assistant for Data Visualization and Storytelling and Data Engineering courses. I enjoy trying my hand in different areas and applying data‑driven solutions to a variety of problems. My background enables me to implement solutions end-to-end, and I’m currently focusing on large language models and the application of agentic AI to new challenges.