Steven Merz is a Senior Data Scientist in Pittsburgh with 11 years of experience bridging chemical engineering research and production-grade data modeling. He holds a PhD in chemical engineering and has a track record of developing predictive and design models for nanoscale self-assembly, overcoming noisy experimental data, long theoretical timescales, and extremely high-dimensional search spaces. At Highmark he applies those quantitative and computational skills to real-world problems, building robust pipelines from simulation and HPC workflows to production analytics. His academic work includes creating custom Monte Carlo and LAMMPS-based simulations, containerizing complex code for HPC, and devising statistical methods that linked MALDI-TOF experiments to theory—skills that translate into practical model deployment and reproducible science. Colleagues describe him as curious, driven, and pragmatic, with a knack for automating repetitive tasks and mentoring junior researchers in version control and collaborative coding.
10 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Chemical Engineering, 3.42, Bachelor's degree, Chemical Engineering, 3.42 at Purdue University
Doctor of Philosophy - PhD, Chemical Engineering, 3.53, Doctor of Philosophy - PhD, Chemical Engineering, 3.53 at University of Virginia
An python module for analysis of LAMMPS copolymer simulations
Contributions:63 commits, 60 pushes, 2 branches in 8 months
lammpspythonsimulationssimulationpython-module
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