Matthew Reeves began data analytics while pursuing a Masters in Music Theory at Boston University in 2009. While many of the techniques are now commonplace in data science today, they were more esoteric at the time and essentially unheard of in the music theory community. In addition to the fact that advanced analytic techniques were unknown, the field of data visualization was still in its infancy. Despite the lack of resources, a number of analytic methods and visualization techniques were developed in order to perform corpus analyses on music and visualize these in multi-dimensional quotient spaces.

He currently works for Wells Fargo as the Lead Implementation Consultant within Artificial Intelligence Enterprise Solution (AIES) group. This group is responsible for assessing, designing, developing, and deploying all AI models within the entire enterprise. As such, there are a large variety of models, ranging from employee work-space and staffing optimization to fraud detection models to chatbots. His responsibilities include design of new AI solutions, data identification and acquisition, data science resource allocation, model approvals and deployment and monitoring. He is also leading the data lake efforts for AI consumption and assisting with feature engineering pipelines for a centralized Global Feature Store.

In addition to working for Wells Fargo, he also consults with a number of companies. He is currently in the process of deploying AI for a produce distribution company in San Diego to help forecast product demand in order to reduce waste and ensure each product is on-hand when needed. He also consults on data projects at The Hub at Davidson College, which is a start-up co-working space in Davidson, NC. He assists questions or problems regarding the any data-related processes and helps guide them based on their needs, skill sets, and understanding.