Kyle Rapp
About Kyle Rapp
Kyle Rapp is an Associate Data Scientist with a strong background in data analysis and economics, holding a Master of Arts from The University of Texas at Austin. He has experience in various roles, including strategic pricing analysis and machine learning model development, and currently works at Advance Auto Parts.
Current Role as Associate Data Scientist
Kyle Rapp currently serves as an Associate Data Scientist at Advance Auto Parts, a position he has held since 2021. In this role, he utilizes advanced data manipulation techniques and programming languages such as SQL, Python, and R to extract insights from relational databases. His work focuses on enhancing data-driven decision-making processes within the company.
Previous Experience at Advance Auto Parts
Prior to his current role, Kyle Rapp worked at Advance Auto Parts as a Strategic Pricing Analyst from 2019 to 2021. In this capacity, he contributed to omnichannel growth and pricing strategies, implementing promotional strategies that leveraged various data sources to improve conversion rates and profit growth.
Education and Expertise
Kyle Rapp earned a Master of Arts in Economics from The University of Texas at Austin, completing his studies from 2016 to 2018. He also holds a Bachelor of Arts in Economics from the same institution, which he completed from 2013 to 2016. His academic background provides a strong foundation for his analytical and data science skills.
Research Assistant Experience
Kyle Rapp served as a Research Assistant at The University of Texas at Austin from 2017 to 2018. During this time, he supported the enhancement of natural language processing capabilities for call centers, utilizing supervised learning techniques and BERT to improve system performance.
Technical Skills and Tools
Kyle Rapp has demonstrated proficiency in various technical tools and platforms essential for data science. He is skilled in using AWS, Hadoop, EMR, and Google Analytics for data analysis and project execution. His expertise also includes developing advanced regression, segmentation, and machine learning models to enhance user experiences in e-commerce.