Foundation
Financial systems
Built deep operational and risk expertise inside one of the world’s most complex regulated environments.
Operations · Lending · Risk
Applied AI · Data Science · Research
I build applied AI systems for consequential decisions.
Two decades in financial services—now extending enterprise rigor into generative AI, environmental research, and human-centered technology.
- Financial systems
- Enterprise AI
- Scientific impact
01 The trajectory
A career built by moving closer to the decision.
Each chapter added a new layer: domain knowledge, quantitative discipline, scalable engineering, and responsible AI.
Evolution
Predictive analytics
Applied statistical modeling to consumer credit and deposit portfolios, turning data into measurable strategies.
Models · Decisions · Outcomes
Scale
Enterprise AI
Led cross-functional AI and machine-learning initiatives spanning automation, NLP, document intelligence, and governance.
AI/ML · Leadership · Delivery
Expansion
Scientific AI
Extended that rigor to environmental research through Harvard graduate work and the NASA GLOBE Program.
Research · Climate · Impact
20+
years in financial systems
28K+
hydrology locations classified
160K
environmental observations supported
02 Enterprise intelligence
From a complex question to a trusted system.
My work lives where technical possibility meets operational reality. The model matters—but so do the data, controls, people, and decisions around it.
01
Frame ambiguous business and risk questions.
02
Build predictive, NLP, and generative-AI solutions.
03
Validate performance with governance and human judgment.
04
Scale the system across teams and workflows.
Applied
AI
System
Data
Models
Risk
People
Value
03 Scientific AI
When enterprise discipline meets citizen science.
Harvard × NASA GLOBE research focused on making crowdsourced hydrology data more consistent, verifiable, and useful at global scale.
01 / Observe
Human measurements carry real-world variation.
Citizen scientists collect hydrology observations across different locations, conditions, and instruments. That scale creates scientific opportunity—and a difficult data-integrity problem.
02 / Curate
AI helps turn variance into verified science.
The research combines classification, statistical validation, and cloud data pipelines to identify anomalies and improve the reliability of downstream environmental analysis.
03 / Share
Research becomes valuable when people can use it.
The GLOBE Curation AI framework moved beyond a graduate project into a public research showcase at the 2026 AI for Good Global Summit in Geneva.
04 Selected work
Systems that connect research, judgment, and delivery.
GLOBE Curation AI
AI-assisted curation and validation for large-scale crowdsourced hydrology data.
- LLM classification
- Bayesian validation
- AWS data pipelines
Responsible AI delivery
Predictive modeling, NLP, document intelligence, and generative-AI workflows designed for regulated environments.
- Python & SQL
- RAG & evaluation
- Human in the loop
Investment Intelligence Lab
A growing suite of applied market-research tools for testing signals, evaluating opportunities, and building informed conviction.
Explore investment tools“
Use data science where the decision matters—and build the trust required to act on it.
My approach to applied AI
05 The throughline
Industry depth.
Academic rigor.
Builder’s curiosity.
I didn’t leave industry to learn data science. I layered increasingly advanced analytics, machine learning, and AI onto two decades of real operational experience.
01Financial servicesDomain depth
02Harvard UniversityGraduate degree · Business Data Science
03Applied researchNASA GLOBE · AI for Good
06 What’s next
Let’s build AI that earns its place in the decision.
I’m interested in consequential problems, thoughtful teams, and systems that move from promising prototypes to trusted outcomes.