AJ Friend
Senior Data Scientist
California, United States
Summary
🤩
Rockstar🎓
Top SchoolAJ Friend is a Senior Data Scientist with 12 years of experience applying convex optimization and algorithm design to real-world systems, currently building Realtime Eater Pricing algorithms for Uber Eats. He blends rigorous applied-math training from Stanford with hands-on back-end engineering, notably contributing Cython bindings and release work to the widely used uber/h3-py geospatial library. His open-source work spans convex optimization tooling (cvxpy) and solver demos (SCS), where he has improved documentation, build stability, and numerical examples—demonstrating a focus on reproducibility and deployability. Comfortable moving between low-level performance tweaks and high-level modeling, AJ has a track record of shipping reliable, production-ready optimization code at scale.
12 years of coding experience
Graduate Student, Applied Mathematics, Convex Optimization, Graduate Student, Applied Mathematics, Convex Optimization at Stanford University
Stackoverflow
763reputation
49kreached
2answers
7questions
Github Skills (29)
python10
sphinx10
cvxpy10
convex-optimization10
geospatial10
c1110
c1710
h310
cython10
linear-programming10
documentation10
optimization10
data-structure9
algorithm9
algorithms9
Programming languages (11)
Github contributions (5)
uber/h3-py
May 2020 - Nov 2022
Python bindings for H3, a hierarchical hexagonal geospatial indexing system
Role in this project:
Back-end Developer
Back-end DeveloperContributions:31 releases, 141 reviews, 193 commits in 2 years 7 months
Contributions summary:AJ was heavily involved in the core development of the `h3-py` library, specifically focusing on the Cython bindings for the H3 geospatial indexing system. Their contributions included the implementation of various H3 API functions, memory management for H3Index arrays, and optimization efforts. They also played a key role in the release process, including versioning, changelog generation, and PyPI deployment steps. The user's work was crucial in enhancing the library's functionality and preparing it for stable releases.
geospatialpythongeocodingpython-bindingsindexing
uber/h3
Jul 2019 - Sep 2022
Hexagonal hierarchical geospatial indexing system
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 release, 246 reviews, 34 commits in 3 years 2 months
Contributions summary:AJ primarily focused on improving the `uber/h3` geospatial indexing system. Their contributions involved clarifying function definitions, removing unnecessary memory allocations, and implementing cell-specific area calculations. Additionally, the user updated and optimized the core algorithms of the library, including functions for calculating edge lengths and iterating cell children. They also worked on updating documentation and adapting code to the latest changes.
hexagongeospatialspatial-indexingindexinghierarchical
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