Jess Ramos is a data analytics educator, LinkedIn Top Voice, and founder of Big Data Energy - a media and education brand with 500,000+ followers across platforms. With an MSBA from the University of Georgia, she turned a corporate analytics career (peaking at $153K at Crunchbase) into a thriving solo business after being laid off in 2023. She runs a Substack newsletter with 45,000+ subscribers, teaches SQL to 50,000+ students via LinkedIn Learning, and has brand partnerships with IBM, AWS, Snowflake, NFL, and Claude (Anthropic). Her origin story - doubling her salary 110% in 11 months - became a viral moment that built her community of data professionals seeking real, human-centric career guidance.
Justin Gage is the founder and writer of Technically, a newsletter that makes software and AI concepts accessible to non-engineers. With 72,000+ subscribers on Substack, he built one of the most respected tech-explainer newsletters from scratch - conceived during a 7-hour Tokyo airport layover - growing it without paid ads through authentic writing and word-of-mouth. By day, he serves as VP of Developer Marketing at Amplify Partners, an early-stage VC firm focused on technical founders.
Carly Taylor is a data scientist, ML engineer, and Field CTO for Gaming at Databricks who blends computational chemistry roots with cutting-edge machine learning to transform how the gaming industry understands player behavior. As founder of Rebel Data Science and creator of the Taylor on Tech newsletter, she advocates fiercely for diversity in data science while holding two ML patents and a track record that includes reducing player churn by 17% at Activision.
Christoph Molnar is a Munich-based statistician-turned-ML-author who turned a side project into the field's most-cited book on interpretable machine learning. Author of six books including the canonical 'Interpretable Machine Learning' (3rd ed., 2025), he runs the Mindful Modeler newsletter and consults on making black-box models explainable. With 16,000+ Google Scholar citations and a PhD from LMU Munich, he sits at the precise intersection where statistical rigor meets machine learning pragmatism.
Eugene Yan is a Principal Applied Scientist turned Member of Technical Staff at Anthropic, where he bridges cutting-edge AI research with production-scale systems. Formerly at Amazon for five years building real-time recommendation and LLM-powered systems for Kindle and Search, Eugene is equally well-known for his prolific writing: 209 blog posts, 420,000+ words published, and a newsletter with over 11,800 subscribers. His open-source repository applied-ml on GitHub has become a canonical reference for teams shipping machine learning in production. He lives in Seattle, snowboards on weekends, and writes like someone who actually wants you to understand.
Hamel Husain is a machine learning engineer with 25+ years of experience who built part of the foundation beneath GitHub Copilot - his CodeSearchNet project was early LLM research later used by OpenAI for code understanding. Today he runs Parlance Labs, consults with AI teams across 35+ products, co-authored O'Reilly's 'Evals for AI Engineers', and teaches thousands of engineers how to move beyond vibes and actually measure their AI systems.
Maarten Grootendorst is a psychologist-turned-ML engineer at Google DeepMind, best known for creating BERTopic, KeyBERT, and PolyFuzz - open-source NLP tools with over 15 million combined downloads. Co-author of the Amazon #1 bestseller 'Hands-On Large Language Models' (O'Reilly, 2024) with Jay Alammar, he runs the 'Exploring Language Models' newsletter with 2M+ views and has taught 50,000+ students on DeepLearning.AI. His work bridges the worlds of psychology and AI, making complex language model internals accessible through strikingly visual guides.
Vicki Boykis is a founding ML engineer and one of the most respected voices in applied machine learning. Known for making complex systems legible through rigorous writing and dry wit, she runs the Normcore Tech newsletter, authored a widely-cited deep dive on embeddings, built Viberary (a semantic book recommendation engine), and created Normconf - an unconventional data conference celebrating the unglamorous realities of ML work. She brings an economist's skepticism and a software engineer's discipline to a field that often confuses hype for progress.
Abdul Ahad is a data consultant and TEDx speaker based in Eindhoven, The Netherlands, with over seven years of experience building data infrastructures for small and medium organisations across e-commerce, insurance, energy, and finance. He is the founder behind KYD Analytics and holds the philosophy of 'Bringing Data and Humans Together' - believing the human element matters more than the tool. In November 2024, he delivered a TEDxEindhoven talk titled 'Why aren't people voting anymore?' exploring how community bonds and incentivisation could revitalise democratic participation. A lifelong learner who codes, consults, and speaks on the stage.