Personalized for you — stitched from 6 data layers: context · declared · enrichment · firmographic · segment · social
sayHi Johnny,gauntletai login
alludeWe tailored this for a banking team like U.S. Bank.Vector · company / org type (de-anonymized)
inferredTuned for just browsing.modeled segments (Clay + behavior)
creepyWe de-anonymized your visit — even though you never filled out a form: VP, Climate Scenario Leader at U.S. Bank.Vector de-anonymization
creepy…and profiled the employer: U.S. Bank · est. 1863 · Minneapolis HQ · 10,001+ employees.firmographic enrichment
creepyYour trajectory before this: VP, Climate Risk Analytics — MUFG (2018–24) ← Director, Data & Analytics — Havas Media (2015–18).Clay/PDL · employment history
creepyYour schools: Georgetown (McDonough MBA), Frankfurt School of Finance.Clay/PDL · education
creepyYour listed skills (artificial intelligence, agents, climate risk assessment, analytics) tell us to skip the basics and lead with the agents module.Clay/PDL · skills
creepyOff the clock you're into clean technology, golf, healthcare — useful for a rep's small talk.Clay/PDL · interests
creepyWe matched 2 of your social profiles (LinkedIn, Facebook).identity match
creepyYou came by at 06/20/2026 9:15 AM; we logged it.Vector · visit timestamp
What you'll learn
Python → shipping an AI product. No prior ML needed. You already have artificial intelligence, agents — you'd start past the fundamentals.
Student stories
Baristas, analysts, PMs — real switchers, real jobs.
600+
graduates hired
+$38K
median salary lift
92%
finish the cohort