Ross Brinkley
About Ross Brinkley
Ross Brinkley serves as the Associate Director of Analytics, Data Operations, Reporting, and Strategy at Rain the Growth Agency. With a background in data infrastructure and business intelligence, he has held various roles in market intelligence and analytics across several companies, contributing to significant improvements in operational efficiency and client engagement.
Current Role at RAIN Agency
Ross Brinkley serves as the Associate Director of Analytics, Data Operations, Reporting, and Strategy at RAIN the Growth Agency. He has held this position since 2022 and operates remotely from Portland, Oregon. In this role, he focuses on enhancing data operations and reporting strategies to support the agency's growth objectives.
Previous Experience in Data Operations
Prior to his current role, Ross Brinkley worked at iNX Commercial Cleaning as the Director of Data Infrastructure and Business Intelligence for 8 months in 2021. He also served as a Senior Market Intelligence Analyst and Lead Generation Architect at the same company for one year. His experience includes significant contributions to data-driven decision-making and operational efficiency.
Background in Market Intelligence
Ross has extensive experience in market intelligence, having worked as the Market Intelligence Manager at Andrews Distributing from 2018 to 2020. In this role, he focused on revenue growth and strategic data insights. His earlier positions include roles at Nielsen as an Associate Client Manager and Retail Analyst, where he engaged in client engagement and sales optimization.
Educational Qualifications
Ross Brinkley holds a Bachelor of Business Administration (B.B.A.) in Marketing from the University of Central Arkansas, where he studied from 2005 to 2008. He furthered his education by obtaining a Master of Science (M.S.) in Marketing Research from The University of Texas at Arlington, completing his studies from 2009 to 2011.
Technical Skills and Contributions
Ross has demonstrated proficiency in data automation and analysis. He automated client performance reports, significantly reducing manual effort and saving over 20 hours per week. He also designed interactive dashboards using Tableau and Datorama, which decreased data analysis time by 25%. His work includes conceptualizing machine learning algorithms for demand forecasting, achieving a 95% accuracy rate.