Alex Jones
President at DSPTCH
Houston, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolAlex Jones is a data-driven founder and president blending storytelling, product leadership, and hands-on scientific software engineering across energy and climate tech. With seven years of experience scaling data science teams at EOG Resources and co-founding DSPTCH—the fastest-growing field service app in wind, solar, and BESS—he focuses on translating complex technical signals into actionable business outcomes. He steers product and engineering strategy while still digging into code and contributing QA and backend work to prominent Julia SciML projects like ModelingToolkit.jl and Symbolics.jl. His work sits at the intersection of statistical modeling, numerical methods, and intuitive visualization, using Python and Julia to uncover “sub-plots” in operational data. Based in Houston, he pairs an MS in Business Analytics from McCombs with a communicator’s instinct for simple, persuasive narratives. Unusually for a president, he continues to write tests and code in open source, keeping his technical edge close to the work.
7 years of coding experience
7 years of employment as a software developer
Master of Science (M.S.) Business Analytics, Master of Science (M.S.) Business Analytics at Texas McCombs School of BusinessBachelor of Science (B.S.) Communication Studies Business Foundations, Bachelor of Science (B.S.) Communication Studies Business Foundations at The University of Texas at AustinCLHS
Github Skills (16)
partial-differential-equations10
symbolic-computation10
differential-equations10
symbolic-computing10
ordinary-differential-equations10
scientific-machine-learning10
julia10
test-automation10
testing10
scientific-computing9
cluster-computing9
computer-algebra9
parallel-computing8
nonlinear-programming8
math7
Programming languages (9)
Github contributions (5)
SciML/ModelingToolkit.jl
Feb 2022 - Jan 2023
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 reviews, 16 commits, 17 PRs in 10 months
Contributions summary:Alex primarily contributes to the `modelingtoolkit.jl` repository, which is focused on scientific machine learning in Julia. The contributions involve modifying core system components, including `PDESystem`, `ODESystem`, and `NonlinearSystem`, which suggests a focus on the underlying equation-based modeling framework. The commits address issues related to mass matrix calculations, testing, and the addition of metadata fields to system structures. The user also implements changes and tests, contributing to the overall functionality and stability of the software.
sdescientific-machine-learningtransformationspartial-differential-equationsdifferential
JuliaSymbolics/Symbolics.jl
Apr 2022 - Apr 2022
Symbolic programming for the next generation of numerical software
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:1 review, 5 commits, 7 PRs in 1 day
Contributions summary:Alex's contributions center around testing and verifying the `symbolics.jl` library's functionality. The commits primarily involve writing test cases to validate array operations, stencil implementations, and the behavior of symbolic expressions within the framework. These tests cover areas such as broadcasting, scalarization, and the application of rules, ensuring the library behaves as expected. The commits show a focus on quality assurance through comprehensive testing of various features.
symbolic-computationsymbolic-computingcomputer-algebra-systemmathematicssql
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