Anna Bethke
Director Of Machine Learning at Phenom
Poynette, Wisconsin, United States
Summary
👤
Senior🎓
Top SchoolAnna Bethke is a director-level AI and data science leader with 15+ years of experience building production ML systems that bridge technical depth and executive strategy. She has led responsible-AI programs and fairness assessments at scale for organizations like Salesforce and Facebook, and currently designs LLM-powered HR analytics and attrition models that drive retention and cost savings. Her background spans applied deep learning (notably NLP preprocessing contributions to IntelLabs’ nlp-architect) to social-impact work enabling ethical AI at Intel, reflecting a rare mix of hands-on model development and policy-minded governance. Anna also teaches AI governance, coaches data scientists, and holds technical credentials from MIT plus an executive MBA, enabling her to translate complex research into practical, auditable solutions. Colleagues rely on her to set methodological best practices and accelerate insight discovery through pragmatic RAG, NLP, and predictive modeling approaches.
10 years of coding experience
15 years of employment as a software developer
Executive MBA, Executive MBA at Quantic School of Business and TechnologyMaster of Science (M.S.) Aerospace Aeronautical and Astronautical Engineering, Master of Science (M.S.) Aerospace Aeronautical and Astronautical Engineering at Massachusetts Institute of Technology
Github Skills (10)
data-preprocessing10
data-loading10
machine-learning10
nlp10
deep-learning10
python10
natural-language-processing10
data-structure9
data-structures9
pytorch9
Programming languages (2)
Github contributions (5)
IntelLabs/nlp-architect
Mar 2018 - Aug 2018
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:74 commits, 1 comment in 4 months
Contributions summary:Anna primarily contributed to the `kvmemn2n` model, adding the `kvmemn2n` data module and associated code for data processing. They implemented data structures, padding functions, and entity extraction utilities for the WikiMovies dataset. This work involved significant interaction with the dataset loading and preprocessing steps within the larger context of a deep learning NLP model.
nlunatural-language-understandingbertlanguage-processingstate-of-the-art
bethke/hermes
Dec 2016 - Dec 2016
Contributions:1 commit, 36 PRs, 110 pushes in 1 day
pythonrecommenderflaskmachine-learningrecommender-system
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.