Summary
Joanne Jordan is a backend engineer and data scientist based in Los Angeles with eight years of experience bridging applied physics, education, and machine learning to build production-ready systems. At CitizenNet (Condé Nast) she applies backend engineering skills to scale data-driven products, drawing on a deep foundation in ML from BloomTech and Lambda School where she also led and taught early data science cohorts. Her background as a high-school teacher and learning specialist uniquely informs her approach to mentorship, curriculum design, and translating complex models into actionable insights for nontechnical stakeholders. Joanne is passionate about applying data science to societal challenges—particularly in education, medicine, and public health—and enjoys connecting with teams that share that mission. A curious problem-solver by training, she blends rigorous analytical thinking from Columbia Applied Physics with hands-on instructional experience to accelerate both team learning and product impact.
8 years of coding experience
2 years of employment as a software developer
Data Science with a specialization in Machine Learning, Data Science with a specialization in Machine Learning at BloomTech
Bachelor of Science (B.S.) Applied Physics, Bachelor of Science (B.S.) Applied Physics at Columbia Engineering