Matt Good

Matt Good

Strategic Pricing Analyst @ Advance Auto Parts

About Matt Good

Matt Good is a Strategic Pricing Analyst at Advance Auto Parts, with a strong background in data analysis and operations research. He holds a Bachelor's degree in Statistics and a Master's degree in Operations Research from North Carolina State University.

Work at Advance Auto Parts

Matt Good has been employed at Advance Auto Parts as a Strategic Pricing Analyst since 2021. In this role, he utilizes his expertise in data analysis and operations research to support pricing strategies. His work involves collaborating with cross-functional teams and engaging with both internal and external customers to drive key business initiatives.

Education and Expertise

Matt Good earned his Bachelor's Degree in Statistics from North Carolina State University, completing his studies from 2014 to 2018. He furthered his education at the same institution, obtaining a Master's degree in Operations Research from 2018 to 2021. His academic background provides a strong foundation in statistical and analytical methods, including coursework in Model & Analysis of Supply Chains and Applied Bayesian Analysis.

Background

Prior to his current position, Matt Good worked at North Carolina Petroleum & Convenience Marketers as an Operations Analyst from 2018 to 2021. He also held a brief role as an Administrator at the same company for three months in 2018. Earlier in his career, he served as a Student-Manager for the Men's Basketball team at North Carolina State University from 2017 to 2018.

Achievements and Certifications

Matt Good is a SAS Certified Specialist in Base Programming Using SAS 9.4. He has completed a successful internship focused on data analysis and operations research, which has contributed to his technical proficiency in various programming and analytical tools, including SAS, R, Python, JMP Pro, MS Excel, Simio, and Matlab.

Skills and Interests

Matt Good possesses skills in Stochastic Modeling in Industrial Engineering and Experimental Statistical Engineering. He is passionate about collecting, analyzing, and defining business and financial data to support management decision-making. His enjoyment of working with cross-functional teams enhances his ability to engage effectively with stakeholders on key projects.

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