Jesse L.
About Jesse L.
Jesse L. is a Junior Data Scientist currently working at Tinuiti in San Diego, California. He holds degrees in Electrical Engineering and Computer Science and has experience in data analysis and research across various organizations.
Work at Tinuiti
Currently, Jesse L. holds the position of Junior Data Scientist at Tinuiti, where he has been employed since 2021. In this role, he focuses on data analysis and modeling to support marketing strategies. His work involves utilizing advanced data techniques to enhance client outcomes in the digital marketing landscape. Jesse's contributions include designing data warehouse infrastructures and collaborating with various teams to optimize data processes.
Education and Expertise
Jesse L. has a solid educational background in engineering and computer science. He earned an Associate's degree in Computer Science from Saddleback College in 2021. Prior to that, he completed a Bachelor of Science in Electrical Engineering at California State University, Long Beach, from 2015 to 2020. Additionally, he achieved a Bachelor of Engineering in Electrical and Electronics Engineering from the University of Wollongong in 2018. His academic training provides a strong foundation for his work in data science and analytics.
Background
Jesse L. has diverse work experience in data analysis and engineering roles. He began his career as a Tutor at Tutoring Club from 2016 to 2018, where he supported students in their academic pursuits. He then worked as a Research Assistant at the University of Wollongong for two months in 2018. Following this, he held an Engineering Intern position at Danone in 2019 and served as an Electronics Engineer: Data Analyst at Northrop Grumman from 2020 to 2021. His experience includes roles that blend engineering and data science.
Achievements in Data Science
Jesse L. has made significant contributions in the field of data science. He designed a data warehouse infrastructure using the open-source workflow management system Prefect, aimed at automating data processes for clients. He built and productionized a Kmeans clustering model to segment buyer transaction data, which enhanced the understanding of customer lifetime value. Additionally, he collaborated with Meta's team to develop business use cases using the marketing mix modeling tool Robyn and supported the development of media mix models using R to predict return on investment.