Jared Storts
About Jared Storts
Jared Storts is a Staff Software Engineer with a diverse background in software development and data science. He has worked at several companies, including BioRender and Labelbox, and has expertise in NLP applications and Generative AI.
Work at BioRender
Jared Storts is currently employed as a Staff Software Engineer at BioRender, a position he has held since 2024. He works remotely and focuses on software engineering tasks that contribute to the company's mission of simplifying scientific communication through visual content. His role involves leveraging his extensive experience in software development to enhance BioRender's platform.
Previous Experience at Streem
Before joining BioRender, Jared worked at Streem as a Staff Software Engineer for 7 months in 2022. His responsibilities included developing and maintaining software solutions within the platform. Prior to this role, he served as a Senior Software Engineer at Streem from 2020 to 2022, where he contributed to various projects in software engineering.
Education and Expertise
Jared Storts holds a Post-Baccalaureate in Computer Science from Oregon State University, which he completed in 2016. He also earned a Master of Education in Educational Assessment, Testing, and Measurement from the University of Oregon in 2005, and a Bachelor of Science in Mathematics from the same institution in 2003. His educational background supports his expertise in software engineering, data science, and artificial intelligence.
Background in Software Engineering
Jared transitioned from a career in teaching advanced mathematics to software engineering. He has worked in various roles, including as a Software Engineer at Jive Software from 2016 to 2017 and as a Senior Engineer in Data Science & AI at Cambia Health Solutions from 2018 to 2020. His experience includes building data pipelines and platforms with a focus on Generative AI and large language models.
Technical Skills and Contributions
Jared has developed expertise in natural language processing (NLP) and machine learning (ML), particularly in creating text analysis applications and recommendation systems. He has utilized Python and the iPython/Jupyter notebook ecosystem to build labs, study designs, and simulations in early data science. His technical skills have been instrumental in his contributions across various organizations.