Richard Mathews II

Halfway through UT Austin's undergraduate program in chemical engineering, I made the decision to pivot into data science because I felt it was a better fit for my curiosity and analytical mindset. Upon graduating in May of 2021, I went to work full-time as a data scientist at the largest chemicals company in the world, BASF. I am participating in their professional development program where I get the opportunity to develop as a data science leader in the chemicals sector. To level up my skillset and broaden my network, I am pursuing a master's degree in data science here at UC Berkeley via the MIDS program.

My current role at BASF is with AI Solutions for Sales, Marketing, and Customer Engagement, where I serve as a global technical lead for the company's churn prediction and market forecasting products. My responsibilities are to oversee the implementation of scalable ETL and ML pipelines in the Azure Databricks platform, develop more accurate and interpretable ML algorithms, and ensure the insights are actively supporting business teams in their decision-making processes. I am also an associate product manager for our market modeling portfolio, where I devise data-driven product strategies for helping business units plan future production with insights into future demand and emerging markets. In addition to these projects, I consult/teach other data science teams in business and manufacturing domains on building scalable data science solutions with Azure, Databricks, and Spark. 

On a more personal note, I am interested in how data science can help humans live better lives. Since my time as an undergrad, I have explored how to be more productive, healthy, and happy using data. I collect over a hundred variables every day on my diet, health, and mood for statistical analysis, as well as to conduct randomized controlled trials for purported health interventions. I have tracked how I spend my time for years, which helps me objectively measure how productive I have been and whether I am allocating my time appropriately to activities that I value.

In essence, data science extends well beyond my professional/academic work into my personal life. Feel free to contact me for a one-on-one discussion about my professional or personal data science work.