About

Mark Christenson is a highly skilled Machine Learning Engineer with over 5 years of relevant experience in the field. Currently, he is working as a Machine Learning Engineer at GoodRx, where he is responsible for developing and implementing machine learning models and tools. Mark holds a Master of Science in Computer Science - Data Science and a Bachelor of Science in Computer Engineering/Computer Science from the University of Southern California. Mark has previously worked as a Backend, Platform, and System Engineer at Ticketmaster, where he was involved in developing backend services in Spring, Vert.x (Java), and Node for a new Ticketmaster web app. He also designed a scalable and resilient AWS system infrastructure for a distributed software system and implemented an automated build pipeline using Gitlab-CI and Kubernetes for a distributed software system. Mark managed an intern and contractor working on Platform and System Engineering tasks and standardized tools to build, deploy, test, and monitor Java-based applications and services. He established automated CI/CD pipelines for Java-based applications and services and championed a company-wide service template for Java services. Mark also designed and implemented architecture within AWS to support Ticketmaster web apps. Before joining Ticketmaster, Mark worked as a Data Engineer at USC Institute for Creative Technologies, where he developed a text classification system to engage users in a question and answer dialogue. He trained and evaluated models and tools for Natural Language Processing and built and automated an ETL pipeline for processing, analyzing, and displaying video in a mobile application. Mark has a diverse tech stack that includes ML, Text Classification, Backend, Data Engineering, Data Scientist, Java, AWS, NLP, ETL, Mobile, Web, Software Engineer, CI/CD, test, Kubernetes, Spring, and infra. With his extensive experience and technical expertise, Mark is a valuable asset to any organization that values innovation and cutting-edge technology.