John Scales
About John Scales
John Scales is a Software Engineer with experience in reverse engineering and machine learning. He currently works at Thomson Reuters and SurePrep LLC, utilizing various technologies and tools in his roles.
Work at Thomson Reuters
John Scales has been employed at Thomson Reuters as a Software Engineer since 2023. In this role, he utilizes a range of tools and technologies, including Git, Azure DevOps, and .NET Core. His responsibilities include both front-end and back-end development, leveraging his skills in JavaScript with React.js and .NET backend technologies.
Experience at SurePrep LLC
Prior to his current position at Thomson Reuters, John Scales worked at SurePrep LLC as a Software Engineer since 2022. His role involved software development tasks, where he applied his knowledge of various programming languages and frameworks. This position has contributed to his overall experience in the software engineering field.
Background in Education
John Scales studied Computer Science at Mt. San Antonio College for 11 months in 2018. He also attended California State University, Fullerton, where he earned a Bachelor of Science in Computer Science from 2018 to 2020. Additionally, he completed an Associate of Science in General Studies with an emphasis in Science and Mathematics at Rio Hondo College from 2015 to 2018.
Previous Role at INDUSTRIAL LOGIC SYSTEMS, LLC
John Scales worked as a PLC Programmer at INDUSTRIAL LOGIC SYSTEMS, LLC from 2020 to 2021. This role involved programming and working with programmable logic controllers, contributing to his technical expertise in software development and engineering.
Technical Skills and Projects
John Scales has developed skills in machine learning using Scikit Learn and has experience in reverse engineering C# and Visual Basic desktop applications. He has also worked on blockchain development projects on Tezos and Ethereum during his personal time. His technical toolkit includes tools such as Jira, Postman, SSMS, SignalR, Linq, Async, AutoMapper, Dapper, and SonarQube.