Cameron Bieganek is a Senior Data Scientist with 11 years of experience applying probabilistic modeling, optimization, and engineering-grade software practices to energy, logistics, and health-data problems. Comfortable across R, Python, and Julia, he has built end-to-end solutions from LightGBM fuel-use models and PyMC Bayesian estimators to JuMP-powered renewables optimizers and CNC toolpath generators. He repeatedly moves research into production—packaging codebases, adding tests, deploying to AWS, and running large experiments on SLURM—while mentoring interns and owning project lifecycles. Notably, his work has driven commercial value (e.g., solar farm layout algorithms contributing to $40M NPV) and practical energy savings models for refrigeration and homes. Based in Minneapolis, he pairs a physics and mechanical engineering background with hands-on software engineering to tackle complex, data-driven physical systems.
11 years of coding experience
10 years of employment as a software developer
M.S., Physics, M.S., Physics at Minnesota State University, Mankato
Master's Degree, Mechanical Engineering, Master's Degree, Mechanical Engineering at Iowa State University
Bachelor's Degree, Physics, Bachelor's Degree, Physics at Denison University
Contributions:33 commits, 21 pushes, 1 branch in 2 months
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