Accolades
2020 World Blockchain Hackathon Mentor. 2020 DE4A Hackathon Winner
2021 Diversity, Equity, and Inclusion in Technology Champion in Tech recipient
2021- 2022 Stanford University Fellow. AAVE Corpus
2022 MIT Press published paper on MLOps, NeurIPS Dataset and Benchmarks submission for NLP paper
2022 NeurIPS Datasets and Benchmarks Reviewer. Global South in AI (GSAI) Workshop Area Chair and Keynote Speaker
2023 Chapter Contributor. “Combating Bias in Large Language Models. Mitigating Bias in Machine Learning. McGraw Hill.
2023 Tulane Alumni Award Equity, Diversity and Inclusion Award Winner
Who I Am
Welcome
Welcome, Friends! It's your favorite neighborhood dreadhead here. I am an accomplished Responsible AI Leader with a history as the Head of Machine Learning at Motley Fool and served as Affiliated Technology Fellow with Stanford HAI. I have ~10 years of experience finding solutions to complex and ambiguous business problems using Machine Learning, Large Language Models, Analytics, and Natural Language Processing. I also have 12 years experience as a public speaker.
Find my projects here or scroll down to learn more about my Data journey.
Data Journey
I am particularly skilled as a Manager, thought leader, Speaker, Data Scientist and Product Owner that has had experience building a Machine Learning team at a Billion Dollar Startup, raising money as a startup advisor and have strong relationships in the AI and VC industry. I am no stranger to meeting strict deadlines, communicating along the way to ensure project cohesion across time zones and mentoring and leading direct reports. In my role as the Head of ML as well as a Senior AI Engineer, I have built strong external relationships with leads and executives across the Tech industry, have managed large budgets and adhered to strict requirements from multi-billion dollar partners. I have led Machine Learning strategy, been the face of Machine Learning at the Motley Fool both internally and externally and feel comfortable communicating both with executives and the general public about complex ideas in a simple way.
Outside of my work experience, I have done research reducing bias in Natural Language Processing and Large Language models and Generative AI, have volunteered to work with Fighting Pandemics leading data curation and teach Fellows from all around the world the skills required to become Data practitioners. This experience has equipped me with the ability to present complex ideas to large audiences and collect open source data for the public.
I have published work on MLOps for policymakers and have presented at conferences in front of industry experts as well as novices in the field. I have created multiple open source datasets including a corpus documented authentic use of African American Vernacular English. This, plus my prior work in Politics makes me comfortable working with policy leaders to get work done. I have written for Medium, Towards Data Science, Decasonic (a VC firm) and have a blog called Progeny of Gradient Descent where I post about AI. I am no stranger to writing about complex topics in a way that is interesting and actionable.