Nicholas Moehle
Quantitative Analyst
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolNicholas Moehle is a quantitative analyst in New York with a decade of experience applying convex optimization, machine learning, and control theory to finance and energy systems. He currently builds portfolio construction solutions at The D. E. Shaw Group after designing exotic portfolio strategies as a VP at Goldman Sachs and leading applied research in BlackRock’s AI Lab. His PhD from Stanford, supervised by Stephen Boyd, produced published work on energy management and underpins a track record of translating advanced theory into production-ready algorithms. Nicholas blends rigorous academic training in mechanical and electrical engineering with hands-on implementation experience from internships at Google to institutional quant teams. He is notable for bridging energy-control research and quantitative finance in ways that improve real-world decision-making under uncertainty.
10 years of coding experience
11 years of employment as a software developer
Bachelor of Science - BS, Mechanical Engineering, Bachelor of Science - BS, Mechanical Engineering at University of California, BerkeleyMaster of Science - MS, Electrical Engineering, Master of Science - MS, Electrical Engineering at Stanford University
Stackoverflow
1reputation
0reached
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Github Skills (32)
python10
cvxpy10
convex-optimization10
mathematical-optimization10
convex10
numerical-optimization10
embedded10
modeling10
optimization10
solver9
model-predictive-control7
svm7
sat7
quadratic-programming6
sat-solver6
Programming languages (4)
Github contributions (5)
moehle/cvxpy_codegen
Jan 2017 - Nov 2017
Contributions:51 commits, 20 pushes, 3 branches in 10 months
code-generationconvex-optimizationoptimizationconvexembedded
moehle/moehle.github.io
Jul 2020 - Jun 2023
Contributions:48 pushes in 2 years 11 months
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