Marlena Duda
Senior Data Scientist, TechOps
Atlanta, Georgia, United States
Summary
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Senior🎓
Top SchoolMarlena Duda is a PhD-trained data scientist and postdoctoral researcher based in Atlanta with 9 years of hands-on experience applying machine learning to large-scale neuroimaging and clinical datasets. She develops ICA-based multimodal fusion methods and time-varying functional dynamics models for applications such as schizophrenia, neurodevelopment, and brain age prediction on cohorts exceeding 10,000 subjects. Her work has produced 11 peer-reviewed papers, multiple invited talks, and cross-disciplinary collaborations spanning academic and industry settings, including an ML internship at Genentech where she built interpretable pan-cancer models. Comfortable bridging deep learning, LSTMs/transformers, and statistical rigor from a dual PhD/statistics training, she focuses on interpretable, clinically-relevant models rather than black-box performance. Outside the lab she teaches fitness classes, reflecting a commitment to translating complex science into accessible practice and maintaining balance between analytic intensity and personal wellbeing. Her rare combination of large-cohort neuroimaging expertise and practical model interpretability makes her especially suited for translational AI in healthcare.
10 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy - PhD Bioinformatics, Doctor of Philosophy - PhD Bioinformatics at University of MichiganBachelor of Science (BS) Biology/Biological Sciences, General, Bachelor of Science (BS) Biology/Biological Sciences, General at Northeastern University
Github Skills (8)
python5
jupyter-notebook5
data-science4
lstm2
machine-learning1
nlp1
deep-learning1
natural-language-processing1
Programming languages (2)
Github contributions (5)
marlenad/GlobalTemporalDerivative
Jan 2020 - Jan 2020
Contributions:4 pushes, 1 branch in 1 day
marlenad/goodreads
Mar 2026 - Mar 2026
code samples for the goodreads datasets
Contributions:5 pushes in 3 days
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