Maria Bernardos is a Data Scientist with eight years of experience applying machine learning and software engineering to scientific and industry problems, currently building time series ML and deep learning solutions at Capgemini Engineering. Trained as an astrophysicist (MS, Universidad Autónoma de Madrid) and seasoned through postdoctoral roles and ESA/observatory projects, she brings rigorous experimental thinking to production-ready pipelines in Python, TensorFlow and scikit-learn. Her background in C++ and scientific software for Cherenkov telescopes gives her uncommon fluency in both low-level performance coding and high-level model design. She has delivered explainable AI for healthcare and energy decision-making, and implemented forecasting systems for pharma e-commerce, showing strength across domains. A self-taught, adaptable engineer, she is passionate about R&D that advances sustainability and environmentally respectful technologies. Colleagues benefit from her blend of academic rigor, practical pipeline development, and a track record of translating complex time series science into actionable business models.
8 years of coding experience
Master of Science - MS, Astrophysics, Master of Science - MS, Astrophysics at Universidad Autónoma de Madrid
Contributions:1 PR, 24 pushes, 1 branch in 5 months
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