Mark Wicks
Data Scientist
Virginia, United States
Summary
👤
Senior🎓
Top SchoolMark Wicks is a data scientist and engineering leader with 13+ years of experience building production ML systems, data platforms, and analytics for enterprise and startup environments. He has led teams to operationalize models—from calibrated random forests for student retention to neural networks for pricing and recommender systems for supplier matching—often deploying services in Docker/Flask on AWS and EMR. Comfortable in both low-level systems (C/C++, network and Linux administration) and big-data stacks (Spark, Hadoop, Hive), he bridges research-grade signal processing and practical product engineering. A former university professor and licensed professional engineer, he combines pedagogical clarity with rigorous modeling practices like isotonic regression and Platt scaling. Currently freelancing, he applies LLMs and embeddings to extract and surface insights from text and build natural language data interfaces, demonstrating a consistent pattern of turning complex academic techniques into business-impacting products.
13 years of coding experience
22 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Electrical Eingineering, 6.0/6.0, Doctor of Philosophy (Ph.D.), Electrical Eingineering, 6.0/6.0 at Purdue UniversityBachelor of Electrical Engineering, Electrical Engineering, Bachelor of Electrical Engineering, Electrical Engineering at University of Dayton
c++, c, xml, tex/latex, lisp, sql, python, go, pytorch, tensorflow
Github Skills (22)
python9
machine-learning9
gpu9
deep-learning8
arch8
statsmodels8
volatility8
stock8
neural-network7
numpy7
finance7
tensorflow7
gpu-acceleration6
tensor6
autograd6
Programming languages (1)
Github contributions (5)
mawicks/PDFiG
Mar 2013 - Mar 2014
Contributions:162 commits in 1 year
mawicks/deep-volatility-models
Mar 2022 - Aug 2022
Contributions:267 commits, 127 pushes, 4 branches in 4 months
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