Mark Bennett
Senior Data Scientist - AI - Financial Services Industry
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolMark Bennett is a Senior Data Scientist specializing in AI for the financial services industry, combining six years of current focused experience at NVIDIA advising on accelerated HPC and ML solutions with two decades of quantitative finance and engineering roles. He bridges systems-level parallel computing and business-facing analytics—authoring NVIDIA articles and sample repos on fraud detection, credit risk, NLP, and explainability while presenting on capital markets and quantum simulation. Previously a senior data scientist and quant at Bank of America, he built production classifiers, deep learning pipelines, and pricing/risk models for derivatives and credit risk. An educator and co-author of a Cambridge-published textbook, he teaches graduate analytics courses and translates academic methods into deployable tooling. Based in Chicago, he’s notable for spanning low-level performance optimization to explainable AI in finance—unlocking revenue by solving problems from compiler-like system drivers up through applied business models.
6 years of coding experience
24 years of employment as a software developer
M.S., Computer Science, M.S., Computer Science at University of Southern CaliforniaB.S. with Distinction, Computer Science, B.S. with Distinction, Computer Science at University of IowaPh.D., Computer Science, Ph.D., Computer Science at University of California, Los Angeles
Github Skills (10)
quantitative9
numba8
rapids8
cuda8
gpu7
dask7
python7
machine-learning7
cudf6
data-science6
Programming languages (1)
Github contributions (4)
nuttty1/S32407
Mar 2021 - Mar 2021
Contributions:42 pushes, 1 branch in 3 days
MarkJosephBennett/fsi-samples
Apr 2021 - May 2021
A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
Contributions:12 pushes, 1 branch in 1 month
cudaanalystpythoncudfleverages
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