James Inlow
Senior Data Scientist I
Minneapolis, Minnesota, United States
Summary
👤
Senior🎓
Top SchoolJames Inlow is a Senior Data Scientist with seven years of experience applying economics-driven insight and creative problem solving—rooted in a double major in Economics and Fine Arts—to production-grade machine learning and automation at LexisNexis Risk Solutions. He builds and maintains internal Python tooling and cloud compute pipelines, authors reusable libraries for model development, and has hands-on experience with large-scale data (100+ GB) using Spark and ECL alongside Python and R. His work spans fraud and credit risk modeling with XGBoost, regularized logistic regression, text mining, and clustering, and he emphasizes automation of reporting and data quality tests to improve team productivity. Colleagues rely on him to translate cross-vertical requirements into practical analytic solutions and documentation that put models into production. Outside of work he brings an artistic sensibility to analysis—he drums, reads deeply, and values thoughtful movies and long walks—which informs a measured, design-minded approach to data problems.
7 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Double Major Economics & Fine Arts, Bachelor of Science - BS, Double Major Economics & Fine Arts at University of Wisconsin-River FallsMaster of Arts - MA, Economics, Master of Arts - MA, Economics at Miami University
Github Skills (74)
xgboost10
python10
pandas10
statistics10
ai10
azure10
rust10
shell10
data-science10
data-structure10
decision-tree10
data-analysis10
machine-learning10
scikit-learn10
data-structures10
Programming languages (10)
Github contributions (5)
jinlow/discrust
Nov 2021 - May 2022
Supervised discretization in Rust
Contributions:1 release, 89 commits, 8 PRs in 6 months
discretizationrustcredit-riskdecision-treesmachine-learning
jinlow/Example_Notebooks
Jan 2019 - Jul 2025
Contributions:15 pushes, 1 branch in 6 years 6 months
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