Summary
Aygalic Jara is a machine learning and data science consultant and PhD candidate based in Paris, with a decade of hands-on experience bridging research and production for precision medicine. Trained with a double degree from Centrale Nantes and Politecnico di Milano in Statistical Learning and Mathematical Engineering, she develops and optimizes deep learning pipelines (PyTorch) for patient stratification and generative models like autoencoders. Her recent work applies foundation transformer models to immunology and federated learning for medical data, combining multidisciplinary collaboration with CI/CD practices and AWS-based model training. She has authored research presented at the American College of Rheumatology and contributed to open-source federated-learning tooling, reflecting a commitment to reproducible, shared science. As a teaching assistant in operating systems and algorithms, she pairs rigorous academic grounding with practical software engineering skills. Beyond publications, her public code—such as a Parkinson’s/breast cancer genome-analysis repo—demonstrates an ongoing focus on translational bioinformatics.
10 years of coding experience
1 year of employment as a software developer
Bac Pro, ELEEC, Bac Pro, ELEEC at Lycée August Escoffier
BTS, SIO, BTS, SIO at Lycée de l'hautil
CPGE ATS, Sciences de l'ingénieur, CPGE ATS, Sciences de l'ingénieur at Lycée Newton
Engineering Degree, Digital sciences for life sciences and healthcare, Engineering Degree, Digital sciences for life sciences and healthcare at Centrale Nantes
Master of Science - MSc, Mathematical Engineering, Master of Science - MSc, Mathematical Engineering at Politecnico di Milano
English, Italian, French