Chang Cai - Economist at Verisk

Chang Cai

Economist at Verisk

Jersey City, New Jersey, United States

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Summary

👤

Senior

🎓

Top School

Chang Cai is a Lead Economist with a decade of experience turning complex spatial and temporal data into actionable policy and planning insights, currently shaping risk and forecasting work at Verisk. He specializes in observational causal inference, computational spatial analysis, and impact evaluation, with applied projects ranging from wildfire-driven tourism effects to ML-enhanced causal forecasts of climate impacts. Chang pairs rigorous academic training (PhD in Agricultural and Applied Economics, MS in Applied Statistics) with production-focused engineering—building scalable ETL pipelines, real-time visitor estimation tools, and forecasting systems adopted by national parks. He also codes in the trenches: front-end contributions to an open-source GraphQL caching tool and a Chrome DevTools extension show a practical ability to translate analytics into usable interfaces. Known for explaining technical results to diverse stakeholders, he blends econometric depth with product-minded delivery to influence infrastructure and conservation decisions. Based in Jersey City, he brings an uncommon mix of spatial econometrics, causal ML, and hands-on software craftsmanship to environmental and commercial risk problems.

10 years of coding experience

6 years of employment as a software developer

Master of Arts - MA, Economics, Master of Arts - MA, Economics at Syracuse University

Bachelor of Arts - BA, International Business/English, Bachelor of Arts - BA, International Business/English at Huazhong University of Science and Technology

Master of Science - MS, Applied Statistics, Master of Science - MS, Applied Statistics at University of Illinois Urbana-Champaign

Github Skills (15)

javascript10

chrome-plugin10

chrome-extension10

chrome-app10

clientside10

webpacker10

react10

browser-extension10

webpack10

html9

css9

wpgraphql8

caching8

graphql8

wordpress-graphql8

Programming languages (2)

TypeScriptJavaScript

Github contributions (5)

open-source-labs/Quell

Nov 2021 - Dec 2021

Quell is an easy-to-use, lightweight JavaScript library providing a client- and server-side caching solution for GraphQL. Use Quell to prevent redundant client-side API requests and to minimize costly server-side response latency.

Role in this project:

Front-end Developer

Contributions:2 reviews, 57 commits, 4 PRs in 21 days

Contributions summary:Chang's commits primarily focus on building the user interface for a Chrome Developer Tools extension related to the Quell project. They are responsible for creating the extension's panel, implementing components like the query input and results output, and integrating a code editor for GraphQL queries. The user also established basic configuration for the extension's webpack setup and implemented caching and network features, demonstrating a focus on user interface design and front-end development within the context of the Quell GraphQL caching library.

cache-controlserver-sidejavascriptapi-requestssessionstorage

Boarde/Sound-Board

Nov 2021 - Nov 2021

This is the Main File

Contributions:69 commits, 34 PRs, 50 pushes in 6 days

javascript

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