Andy Walsh
About Andy Walsh
Andy Walsh is a Data Scientist at 80 Acres Farms in Cincinnati, Ohio, where he has worked since 2021. He specializes in automated data processing and visualization, and has developed a custom Python package for purchase order decision making.
Work at 80 Acres Farms
Andy Walsh has been employed as a Data Scientist at 80 Acres Farms since 2021. In this role, he has led reporting initiatives for the Procurement, Maintenance, and Sustainability groups. His work focuses on automated data processing and visualization, utilizing Power BI to enhance data accessibility and insights. Walsh has also developed a custom Python package aimed at automating purchase order decision-making, which is deployed on Azure Databricks.
Previous Experience in Data Science
Before joining 80 Acres Farms, Andy Walsh worked as an Applied Data Fellow at Cook County Government from 2020 to 2021. His role involved applying data science techniques to support various projects. Additionally, he interned at TRADEWEB MARKETS INTERNATIONAL LLC in 2018, where he gained experience in market data analysis. He also served as an Energy BLM Intern at CME Group from 2019 to 2020, where he implemented Sklearn regression models to estimate product loss during mixing and packaging processes.
Education and Expertise
Andy Walsh studied at the University of Chicago from 2016 to 2020, where he earned a degree in Physics. His educational background has provided him with a strong foundation in analytical thinking and problem-solving. In his professional roles, he has utilized various data processing tools and libraries, including PySpark, Pandas, and NumPy, to develop custom Python packages for data analysis.
Technical Skills and Tools
In his data science roles, Andy Walsh has demonstrated proficiency in several technical skills and tools. He has experience with automated data processing and visualization using Power BI. His expertise includes developing custom Python packages and implementing machine learning models using Sklearn. Walsh has also utilized Azure Databricks for cloud-based data processing, showcasing his ability to work with modern data infrastructure.