Jake Huneycutt
About Jake Huneycutt
Jake Huneycutt is a data scientist with extensive experience in various roles across multiple companies, including Cadillac and Aquent. He holds an MBA from Emory University and has a strong background in data analysis, machine learning, and software engineering.
Work at Cadillac
Jake Huneycutt has been employed as a Data Scientist at Cadillac since 2022. In this role, he applies his expertise in data analysis and machine learning to support various projects within the organization. His contributions focus on enhancing data-driven decision-making processes and improving operational efficiencies.
Experience at Aquent
Since 2022, Jake Huneycutt has also been working as a Data Scientist at Aquent. His responsibilities include leveraging advanced analytics to provide insights that drive business strategies. His role involves collaboration with cross-functional teams to develop data solutions that meet client needs.
Previous Role at Cracker Barrel
Before joining Cadillac, Jake Huneycutt worked at Cracker Barrel as a Data Scientist in Advanced Analytics and Financial Planning & Analysis from 2021 to 2022. During his time there, he focused on utilizing data to inform financial strategies and operational improvements within the company.
Educational Background
Jake Huneycutt holds a Bachelor of Arts degree in History and Political Science from East Tennessee State University. He furthered his education by obtaining an MBA with a focus on Finance and Data & Decision Analysis from Emory University's Goizueta Business School. Additionally, he studied Computer Science at BloomTech and earned a Master of Accounting (MAC) from UNC Kenan-Flagler Business School.
Technical Skills and Expertise
Jake Huneycutt is proficient in programming languages such as Python, SQL, and JavaScript. He has extensive experience in data visualization tools including Vega, D3, Tableau, and PowerBI. His technical skills also encompass building web applications using Vue.js and Nuxt frameworks. He has worked on various machine learning projects, including recommender systems, image classification, and natural language processing.