Summary
Jennifer Stiso is a Lead Machine Learning Research Scientist with nine years of experience translating complex biological, clinical, and social datasets into actionable models and products. With a PhD in neuroscience from UPenn and a track record across academia, healthcare, and industry, she builds interpretable dynamical systems, network, and time-series models that have driven multi-million dollar impact in production. She combines hands-on skills in Python/R, SQL, MLflow, and AWS SageMaker with software engineering practices—unit tests, pipelines, and deployment via Airflow—to ensure reproducibility and reliability. Jennifer excels at communicating nuanced methodological trade-offs to diverse stakeholders and has a history of turning research-grade methods into operational tools for clinicians and business teams. An unexpected strength is her experience scaling attention-based long-sequence models (from 1,000 to 3,400 tokens) to improve clinical coding and revenue prediction while retaining interpretability.
9 years of coding experience
8 years of employment as a software developer
Bachelor's Degree Cognitive Science and Molecular and Cell Biology, Bachelor's Degree Cognitive Science and Molecular and Cell Biology at University of California, Berkeley
BA Molecular Biology & Cognitive Science, BA Molecular Biology & Cognitive Science at University of California at Berkeley
PhD Computational Neuroscience, PhD Computational Neuroscience at University of Pennsylvania
English