Hi, I’m Dan Shiebler. I like math, history podcasts, fantasy novels, riding my bicycle, and traveling. I live in NYC.
Today I work as the Head of Machine Learning at Abnormal Security, where I lead a team of 50+ engineers and data scientists building the world’s most advanced messaging cyberattack detection system.
Before joining Abnormal Security, I worked at Twitter — first as a Staff ML Engineer on the Cortex team, where I built Twitter’s core vector search and entity embedding capabilities, and later as the Engineering Manager for the web ads ML team, which powered Twitter’s $1B+ ARR web ads product.
Prior to Twitter I was a Senior Data Scientist at TrueMotion, where I designed many of the patented sensor data analytics algorithms that contributed to TrueMotion’s $650M acquisition.
I hold a DPhil (PhD) from the University of Oxford, where I used category theory to develop novel perspectives on vector embeddings, clustering, and optimization algorithms. I was advised by Jeremy Gibbons and my thesis title was Compositionality and Functorial Invariants in Machine Learning. I also hold Bachelor’s degrees in Neuroscience and Computer Science from Brown University.
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