Morgan Natham

Morgan is a Vice President in Accordion’s Data & Analytics practice with more than seven years of experience applying data science, machine learning, and AI to complex business problems across the sports, banking and financial services, and consumer beauty sectors. Morgan partners with clients to turn data into strategic and operational insight, using advanced analytics, predictive modeling, and AI-enabled solutions to improve performance and support better decision-making. Morgan’s technical toolkit includes Python, R, SQL, XGBoost, Random Forests, LLMs, AI agents, Claude, Copilot, Airflow, and CI/CD.

At Accordion, Morgan delivers end-to-end data and AI solutions for clients, from building predictive models and scalable data infrastructure to providing insights that inform strategy and operations. Morgan currently supports one of the largest hair removal providers in the U.S., where Morgan developed a store segmentation through cluster analysis and built forecasting models for guest visits. These forecasts power a user-facing application that helps center leaders optimize scheduling and hiring and identify labor gaps before they affect operations.

Prior to joining Accordion, Morgan spent 3.5 years at KPMG in Los Angeles, advising banking clients on fraud detection and financial crimes risk. Morgan built a third-line anti-money laundering (AML) machine learning model to detect suspicious activity, which served as an independent challenger to the first-line production model. Across multiple audits, the challenger model surfaced new suspicious transactions and customer activity, including several transactions the production model had missed, strengthening the clients’ model validation and compliance processes.

Morgan began a career in sports analytics as an intern with Nashville SC, analyzing opponents’ throw-in patterns to inform pre-match scouting reports for the technical staff and using Transfermarkt data to identify high-upside, low-cost players in smaller markets. As an Associate Quantitative Analyst with the Los Angeles Dodgers, Morgan was responsible for maintaining all production models, including monitoring nightly Airflow pipelines, resolving issues, and conducting code reviews. Morgan also introduced Docker and CI/CD across the organization, standardizing production processes and training colleagues on coding best practices.

Morgan holds a Bachelor of Science in Mathematics with a minor in Economics from Bowling Green State University and completed Galvanize’s 13-week Data Science Immersive program.