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 (13)
deep-learning8
machine-learning8
python8
gpu8
numpy7
time-series7
neural-network6
tensor6
gpu-acceleration6
autograd5
dataannotations2
jupyter-notebook1
data-annotation1
Programming languages (1)
Github contributions (5)
mawicks/PDFiG
Mar 2013 - Mar 2014
Contributions:162 commits in 1 year
mawicks/mvarch
Mar 2022 - Oct 2022
Multivariate Volatility Models (ARCH) for stock prices and other time series
Contributions:2 releases, 229 commits, 58 PRs in 7 months
time-series
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