Dr. Carlos Zetina — industrial engineer, ex-Amazon research scientist, and pre-sales consultant at FICO — walks through how he thinks about problems before solving them. Drawing on his PhD in optimization, years in risk consulting, and three intense years at Amazon, Carlos shares the frameworks he uses to make sure organizations work on the right problems, not just the loudest ones. The conversation covers what pre-sales engineering actually is, why documentation is the foundation of good AI adoption, and how the rise of generative AI is shifting the most valuable work from authoring to monitoring.
Chapters
0:00 - Preview
1:00 - Meet Carlos Zetina & career overview
5:23 - What working in Amazon is actually like
7:26 - How to identify & prioritize the right problems before building anything
10:22 - Operational planning cadence
14:13 - Decision framing: Why Carlos's first ML model completely missed the mark
17:32 - What is pre-sales engineering?
19:30 - Push vs pull systems
23:59 - Should you join pre-sales?
27:41 - Post-sale knowledge transfer
33:50 - Gen AI & why writing culture becomes a strategic asset
37:45 - The future of OR and data science with GenAI
Follow the show
Apple: https://podcasts.apple.com/in/podcast/the-decision-intelligence-lab/id1811085064
Spotify: https://open.spotify.com/show/0lFoAVKqJHTYSZNpeN61ou?si=0ae973aab0174b3b
Connect with guest
Carlos Zetina: https://www.linkedin.com/in/cazetina/
Connect with hosts
Prof. Vijay Mehrotra (University of San Francisco): https://www.linkedin.com/in/vijay-mehrotra-ba9498/
Prof. Michael Watson (Northwestern University): https://www.linkedin.com/in/michael-watson-07600a1
About the podcast
The Decision Intelligence Lab podcast delivers real-world insights for data professionals, business leaders, and anyone seeking to leverage data & AI for smarter decision-making & successful business outcomes.
For business inquiries, email at decisionintelligencepodcast@gmail.com
