Data Scientist · Ex-Google · PhD Economics
Hello, I'm Sophia Chen. I build and write about AI-native data science.
More than a decade of turning ambiguous business questions into measurable impact—from metrics strategy and causal measurement to forecasting and AI-native analytical systems.
Selected writing
Recent articles
Oct 7, 2026
Building a Forecasting Agent Platform, Part 2: Agentic Forecast Workflow
Designing and Building an AI Agent to Orchestrate, Execute and Narrate Forecasting Workflows.
Jul 5, 2026
Building an AI-Native Causal Agent Platform: From Prototype to Production
An End-to-End Agentic Workflow for Causal Analysis.
Sep 16, 2025
From Data to Decisions: A Practical Framework to Quantifying Business Impact
Using a Tiered Approach to Inform Investment Strategies.
Building
S-Curve Data
Specialist AI agents for rigorous analytical problems, built so the assumptions, diagnostics, uncertainty, and validation stay visible.
- Causal Inference Live
- Forecasting Live
- Predictive Modeling In development
- Experimentation In development
About
For more than a decade, I've worked at the intersection of data, products, and business decisions. I started in credit and mortgage risk modeling at Fannie Mae and Moody's Analytics, then moved into product data science—first at Intuit, where I helped build the experimentation culture and product data science foundation for QuickBooks Checking, and later at Google, where I defined the success metrics framework and led cross-functional business reviews for Google Maps Platform. I'm now back at Intuit, building predictive ML models and AI-native data science capabilities. The through line has always been the same: using rigorous analysis to help teams decide what to build, how to measure it, and what to do next.
That experience shapes my independent work through S-Curve Data, where I explore how to make data science workflows AI-native—using AI to improve productivity, strengthen analytical rigor, and amplify business impact. I write about the frameworks and practices behind that transformation.
Outside of data, I'm also building Southern Frontier, a modern Pu’er tea brand.
Experience
- 2026 - Present
Data Scientist · Intuit Current
Build predictive ML models for QuickBooks Services products and help establish an AI-native MLOps process covering the full model lifecycle—from training and deployment to monitoring—reducing model development time from months to days.
- 2025 - Present
Data & AI Writer · Medium Independent
Write about AI-native data science, causal inference, forecasting, experimentation, product analytics, and the process of building rigorous analytical systems with AI. Read my articles at medium.com/@sophiashunqinchen
- 2025 - Present
Founder · Southern Frontier Independent
Founded Southern Frontier, a modern Pu’er tea brand bringing ancient-tree tea traditions into contemporary everyday life. Built the product, brand, and physical experience, including our flagship tea house in Hangzhou, China. Visit us at www.southernfrontiertea.com
- 2022 - 2025
Data Scientist · Google
Defined success metrics framework and led cross-functional business metrics reviews for Google Maps Platform. Built foundational data infrastructure, core ML forecasting capabilities, and self-service analytics tools.
- 2020 - 2022
Data Scientist · Intuit
Spearheaded experimentation culture (A/B testing) and 0-to-1 product data science capabilities. Drove key insights for growth in QuickBooks Checking.
- 2019 - 2020
Research Associate · Moody's Analytics
Managed client relationships and delivered high-stakes credit risk modeling solutions and leading ML interpretability techniques for enterprise customers.
- 2015 - 2019
Quantitative Modeler · Fannie Mae
Developed and validated complex transition models and ML models for mortgage-backed securities portfolio management.
Education
- Ph.D. in EconomicsThe George Washington University
- B.A. in EconomicsZhejiang University