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David Betancourt, Ph.D.
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David Betancourt, Ph.D.

Head of AI at DB Macro Research

Key Expertise
enterprise ai saas disruption; agentic ai autonomous systems; ai in financial services

David Betancourt, Ph.D.

Head of AI at DB Macro Research

About

David Betancourt, Ph.D. is a computer scientist, engineer, and tech entrepreneur with 15+ years building production AI systems in complex, high-stakes environments where reliability, scalability, data privacy, security, and observability are first-class citizens. He leads AI/ML for portfolio management and market analytics software at DB Macro and previously led privacy-preserving on-device ad personalization for Apple App Store Ads. He holds a Ph.D. in CS / Machine Learning from Georgia Tech, where his research focused on uncertainty quantification in deep learning and reinforcement learning. He consults on GenAI and agentic AI, AdTech, AI scalability, and strategic themes including the future of finance, the AI trade, physical AI/robotics, and the future of SaaS in an agentic world.

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QUICK FACTS

LOCATED IN

New York, NY

LANGUAGES

English

Education

Ph.D., Computer Science / Machine Learning, Georgia Institute of Technology (research focus: uncertainty quantification in deep learning and reinforcement learning)

What You Can Learn From This Expert

Here are the disciplines, strategies, and frameworks this expert can help your team master.

The models, architectures, and engineering work behind modern AI systems, including large language models, agentic systems, and AI product development. Experts here help clients separate real technical capability from hype.

The competitive, financial, and go-to-market forces shaping the AI industry, from frontier labs to enterprise vendors and investors. Experts here help clients read the market and make sharper strategic and investment decisions.

How AI is being applied within specific industries, including financial services, healthcare, and other specialized sectors. Experts here bring domain depth alongside technical fluency.

The financial mechanics of running AI at scale, including compute and infrastructure spend, model performance versus cost trade-offs, and budgeting for AI initiatives. Experts here help clients make sharper build, buy, and spend decisions as AI costs scale with use.

How organizations measure and capture the return on their AI investments, from cost savings and productivity gains to new revenue creation. Experts here help clients move past pilot-stage excitement to prove and defend measurable business impact.

Career History

Careers Timeline

Dec 2024 – Current

Founder & CEO — Reinforce Market Labs

 

May 2024 – Current

Head of AI & Founder — DB Macro Research

Leads research and production deployment of agentic systems combining multi-agent architectures, fine-tuned LLMs, and reinforcement learning to support high-stakes decision-making across portfolio workflows.

 

Sep 2020 – May 2024

AI/ML Scientist, Applied Research — Apple Inc.

Led cross-functional development of privacy-preserving on-device AI for App Store Ads personalization, including federated learning infrastructure and an experimentation/measurement platform.

 

Jun 2015 – May 2024

Founder and Portfolio Manager — DB Macro

 

Mar 2019 – Mar 2020

Chief Scientist — Vorstella Corp.

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