Work

In my current role, I continue to work on homeowners insurance pricing models while building tools for monitoring production data and detecting drift. I enjoy improving workflows and reducing repetitive manual work through automation. Recently, I transitioned many Jupyter notebook-based workflows into modular Python scripts and used SageMaker Pipelines to help automate training and validation processes.

During my internship, I protyped homeowners insurance rating models using GLM and GBM models with Python and AWS SageMaker. During this internship, I learned the importance of interpretable model, which can be preferred over model optimized soley on predictibility. I also learned different ways to handle missinge values and how to work with large-scale datasets.

I led the administrative team as a Sergeant-in-Charge, overseeing the unit’s adminsitrative processes, and supporting day-to-day logistical and operational needs. I also graduated Air Assault School, which is one of the most memorable experiences of my life.