Summary
Leonie Chevalier is a Junior Software Developer with nine years of experience blending astronomy-focused data science and practical machine learning engineering. Based in Greater Melbourne, she applies a research-driven approach from her MS in Astronomy and Astrophysics to build robust data workflows and production-ready models, having worked on ML data augmentation and integration at Silverpond and ongoing development at ADACS. Comfortable both collaborating in teams and driving projects independently, she excels at turning complex, noisy scientific datasets into actionable solutions. Her background gives her a unique aptitude for rigorous experimentation and reproducible pipelines, useful in both research and industry settings.
9 years of coding experience
Master of Science - MS, Astronomy and Astrophysics, Master of Science - MS, Astronomy and Astrophysics at University of Sussex
Bachelor of Science - BS, Astronomy, First, Bachelor of Science - BS, Astronomy, First at University of South Wales
Astronomy and Astrophysics, Astronomy and Astrophysics at Swinburne University of Technology
International Baccalaureate, International Baccalaureate at Malvern College
English, German