qiuya@datascience — profile

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Qiuya Xu

Senior Data Scientist · Applied Statistics

QX

I build machine learning and causal inference systems that turn complex data into reliable business decisions. My work spans LLM-powered classification, fee accuracy, marketplace measurement, and executive metrics at global scale.

$ view_work resume.pdf email
> current_focus:LLM annotation · product classification · causal inference · business measurement
01

Experience

Amazon

Senior Data Scientist

  • Launched a worldwide Transformer-based product classification model, eliminating $310M in fee errors and benefiting 400K sellers.
  • Built an LLM annotation solution that handles 82% of human workload at ~97% accuracy.
  • Automated causal impact analysis for fee changes, reducing assessment time by 66%.
  • Developed Weekly Business Reviews for merchant-fulfilled programs across adoption, conversion, and revenue.

comScore Inc.

Senior Data Analyst

Advanced Mobile Metrix methodology, developed automated QA and visualization tools, and applied statistical models to panel health and collection completeness.

02

Selected Work

PROJECT / 01

Bad Categorization · ATLAS

Worldwide fee-category classification and LLM annotation workflow, improving high-precision coverage by ~30% while automating 82% of human annotation.

LLMTransformers97% accuracy

PROJECT / 02

Marketplace Intervention · REMI

Causal impact measurement for fee changes across units, revenue, selection, and ad spend—with an automated workflow that reduced analysis time by 66%.

Causal inferenceSynthetic controlAWS

PROJECT / 03

Android Browser Usage Model

Matched Android devices using app-overlap distance metrics to estimate browser traffic, keeping error within 7% for most top entities.

Statistical modelingMobileMeasurement

PROJECT / 04

Recommendation Systems

Built article and URL-level recommendations for anonymous users using logistic regression, classification trees, and collaborative filtering.

RecommendationClassificationResearch
03

Technical Stack

AI / ML

LLMs, classification, recommendation, collaborative filtering, machine learning

Statistics

Causal inference, synthetic control, regression, Bayesian methods, experiment measurement

Data & Infra

SQL, AWS EC2, databases, high-performance computing, data visualization

Languages

Python, R, SQL, SAS

04

Education

Cornell University

M.P.S. in Applied Statistics · GPA 4.1/4.3

Sun Yat-Sen University

B.S. in Statistics · GPA 3.7/4

Let’s solve something complex.

Interested in data science, causal measurement, and machine learning systems with real business impact.

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