Chase Joyner

Background

About Chase Joyner

Model development, experimentation design, data analysis, and presenting results to senior leaders, business partners, and model validators with a track record of delivering successful outcomes. • Machine Learning, Random Forest, Boosting, Neural Networks, Natural Language Processing, Large Language Models, Generative AI, Transformers, Classification, Regression, Penalized Regression, Timeseries, Markov chain Monte Carlo, etc. • Python, PySpark, PyTorch, CI/CD, R, SQL, GitHub, Databricks, AWS, Azure, LaTeX, Excel, etc. • Experience in applying machine learning techniques in the technology sector. • Background in credit risk modeling, with applications in CCAR and CECL. • Passion for standardization and automation of processes for efficient and accurate modeling.