Alana G
Protection Scientist at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAlana G is a protection scientist and applied data scientist in San Francisco with six years of experience tackling fraud, abuse, and trust-and-safety challenges across major tech platforms. Currently at OpenAI, she brings production-focused anti-abuse expertise honed through senior roles at Twitter and YouTube and early work at Smyte and Google. Her background spans hands-on modeling, product management, and operational strategy, enabling her to translate policy needs into robust, scalable detection systems. As a freelance data consultant she sharpened cross-industry problem solving and delivery skills, and she contributes to open-source ML tooling—most notably helping maintain DeepChem’s models and infrastructure. Collected academic training from Stanford underpins her analytic rigor, while her blend of product and engineering experience means she often bridges the gap between research prototypes and auditable production systems. She’s known for quietly improving developer workflows and fixing thorny infrastructure issues that keep safety systems reliable at scale.
7 years of coding experience
8 years of employment as a software developer
Bachelor of Arts (BA), Bachelor of Arts (BA) at Stanford University
Github Skills (10)
pytorch10
machine-learning10
deeplearning-ai10
deep-learning10
python10
drug-discovery9
quantum-chemistry8
biology8
science8
jupyter-notebook7
Programming languages (9)
Github contributions (5)
deepchem/deepchem
Sep 2020 - Aug 2021
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Role in this project:
ML Engineer
ML EngineerContributions:54 reviews, 17 commits, 33 PRs in 11 months
Contributions summary:Alana primarily contributed to the development and maintenance of machine learning models and related tooling within the DeepChem library. Their work included fixing deprecation warnings in example notebooks, adding deprecation warnings to existing transformers, and refactoring code. They also addressed minor issues like fixing a typo in a class name, merging branches, and updating documentation related to the infrastructure.
deep-learningquantum-chemistrydrug-discoverybiologymaterials-science
alat-rights/deepchem
Jun 2021 - Aug 2021
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Contributions:8 PRs, 89 pushes, 13 branches in 2 months
deep-learningquantum-chemistry
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