About

The long version is that I started my career in engineering after graduating from University of Wisconsin Platteville with a BS in Mechanical Engineering.

I first started using analytics and data science to optimize processes, and increase performance of equipment in the manufacturing setting. From there I expanded into price optimization, capital forecasting, and new business development.

I started working for Tuft and Needle in November of 2021 as a Data Engineer, where I specialized in developing ETL solutions, building models and deploying them into production using AWS.

In May of 2022 I joined Epsilon as a Senior Data Scientist, here I have (and continue) to work on developing full stack data science solutions for our customers, as well as improving the data science technology, and process for the rest of the team. 

Starting in January of 2021, I began working on my MS in Data Science and finished in December of 2022. 

In this program we covered, big data tools like Hadoop and Spark, AWS cloud computing systems. Then machine learning algorithms like Artificial Neural Networks, Principle Component Analysis, clustering, and boosted decision trees. We also did a deep dive into statistics and how they relate to data cleaning, imputation and data science in general. My favorite course was prescriptive analytics, which centered on decision theory, and optimizing systems using random walk and genetic algorithms. 

My capstone was on “The Impacts of Supply Chain Volatility on Price Elasticity” with an emphasis on how the COVID-19 and the Ukrainian conflict took highly subsidized commodities and made them elastic for specific periods.

Want to check out my portfolio and take an even deeper look into the work? Click the portfolio button below!