Eduardo Ariño de la Rubia
I teach AI, deep learning, NLP, and the design of analytics projects in the MSc in Business Analytics program at Central European University in Vienna — ranked #1 in Central Europe. My job is to make sure students leave the classroom able to actually do the work, not just talk about it.
Before CEU, eight years at Meta — Senior Director of Infrastructure Foundation analytics, plus earlier work in Reality Labs (Quest, Ray-Ban Metas, FAIR) and Integrity at Facebook & Instagram. Earlier still: Chief Data Scientist at Domino Data Lab, and principal data science / robotics work at Ingram Content.
Agentic resume tailoring + cover letters + interview prep
A Claude Code skill that tailors resumes and writes cover letters for specific jobs by mining evidence from your actual project folder — not the resume you wrote a year ago. Built for my students, usable for everyone.
Backup, search, and remix your Ultimate Guitar library
CLI tool to back up, explore, and build setlists from your Ultimate Guitar tabs. Features AI-powered similarity matching and thematic medley building — turn a 5,000-song library into a useful instrument.
Privacy-first PWA for charting life events and their consequences
An open-source, client-only Progressive Web App that helps you build a personal graph of life events and their downstream repercussions. Nothing leaves your device.
TL;DR: After 8 years at Meta, I'm starting a new chapter as Professor of Practice at Central European University (CEU) in Vienna — teaching, building, and staying hands-on with AI. CEU is a rare institution: global in outlook, committed to academic freedom and critical thinking. This is the move.
553 reactions · 119 comments
This paper from Anthropic is so valuable in my role as Professor of Practice at CEU. My first reading: using AI while learning a new technical skill can measurably reduce actual understanding, even when it doesn't reliably reduce performance. That gap — between what you can do with the tool and what you actually know — is the whole pedagogical problem of this moment.
266 reactions · 18 comments
Nobody told me the job was running 1:1s, aligning roadmaps, writing growth plans, sitting in calibration meetings arguing over whether someone's work was 'senior-level' or just very strong mid-level. I figured it out eventually — by being a mediocre manager for longer than I'd like to admit, while good people depended on me to be better. So I taught a two-day intensive at CEU compressing that learning, and open-sourced the whole course.
94 reactions · 13 comments
This fall I taught ECBS5294 at CEU — SQL, JSON normalization, reproducible pipelines — a required core course in the MSBA program. The practical data skills I spent years learning piecemeal. I'd spent months building it out with AI as a true co-author. What surprised me wasn't speed. It was the quality of the back-and-forth.
52 reactions · 12 comments
Not because the people are bad at statistics. Because nobody asked: What decision does this actually inform? What breaks if we succeed? Who might block us, and why? I've been teaching a course at CEU called Designing Analytics Projects on exactly this — the work that has to happen before the code.
43 reactions · 12 comments