Parker Erickson

Parker Erickson has a diverse range of work experience in the technology industry. Starting in 2019 as a Software Engineering Intern at Optum, Parker developed a fraud detection system utilizing graph databases and machine learning. This project is currently patent-pending. In 2020, Parker joined Optum as a Software Engineer, focusing on combining machine learning with the Health Care Knowledge Graph. They also created an internal portal for an enterprise mandated product during their software engineering internship at Optum.

In 2021, Parker transitioned to TigerGraph as a Data Science/Machine Learning Intern, contributing to various graph algorithms and assisting in the development of the pyTigerGraph Graph Data Science module. They also presented a demo with external partners and conducted a workshop at the Graph+AI Summit conference. In 2022, Parker advanced to the role of Machine Learning Engineer at TigerGraph, where they implemented supervised and unsupervised embedding approaches for graph data using Python and GSQL. They also devised a patent-pending in-graph feature store solution, which resulted in significant downloads of approximately 3,000 per week.

Prior to their technology positions, Parker gained experience as a Retail Sales Specialist at REI from 2016 to 2020.

Parker Erickson completed their education as follows:

From 2014 to 2018, Parker attended Robbinsdale Armstrong High School for their secondary education.

Subsequently, they pursued higher education at the University of Minnesota. From 2018 to 2021, Parker obtained a Bachelor of Science (BS) degree in Computer Science from the University of Minnesota.

Following this, Parker continued their studies at the University of Minnesota and obtained a Master of Science (MS) degree in Computer Science from 2021 to 2022.

In addition to their formal education, Parker also obtained certifications in GSQL 101 and Graph Algorithms for Machine Learning from TigerGraph in December 2020.