About

Working between the decision and the system.

My work begins with a business or policy problem, moves through data and implementation, and ends with a precise account of what the result can—and cannot—support.

A practical route into AI implementation

I am Wuhao Xia, an MPA candidate in Data Science for Policy at Columbia University’s School of International and Public Affairs. I expect to graduate in May 2027.

My experience spans international development research, consulting, business analysis, and data science. It has taught me to look beyond whether a model works in isolation: where it fits in a workflow, what evidence a user needs, how quality is judged, and when a person should take over.

I am pursuing roles in AI adoption and implementation, AI strategy consulting, and applied data science or business analytics.

What I contribute

01

Problem framing across functions

I translate business or policy requirements into the data, software, and review process needed to address them.

02

Hands-on implementation

I work directly in Python, SQL, analytical models, data pipelines, and lightweight applications rather than stopping at a recommendation.

03

Evidence-aware judgment

I define baselines, inspect uncertainty, and distinguish measured results from projections and design intent.

Education

Columbia University
Master of Public Administration
Data Science for Policy concentration
University of Florida
Bachelor of Science in Information Systems
Minor in Economics

Selected experience

World Bank Group
AI-enabled research workflows, evidence review, and cross-country regulatory analysis
Bain & Company
Industry, digital infrastructure, product, and regulatory research
Capgemini
Business analysis, data processing, forecasting, and workflow design
Siemens
Commercial analytics, forecasting, and automated reporting

Contact

Discuss an opportunity or a problem worth implementing.