Matthew
Nelson,
PhD

Conduct quantitative research for Amazon's Reputation Marketing & Insights team — measuring brand perception, executive favorability, and competitive standing globally.

• Design and execute large-scale survey programs tracking reputational outcomes over time
• Build automated data pipelines and reporting infrastructure; deliver crosstab tables, visualization decks, and research briefs to senior communications and marketing stakeholders
• Conduct logistic regression with Shapley value decomposition and specification curve robustness checks to model reputation outcomes; apply factor analysis and correlation analysis to identify latent drivers of brand perception
• Manage cross-vendor methodology, data quality review, and calibration to ensure data integrity across research partners
• Apply machine learning and AI tools to automate data processing and synthesize insight at scale

Delivered quantitative research and strategic counsel for Fortune 50 companies navigating reputation risk, competitive pressure, and crisis communications.

• Designed survey instruments and statistical models informing high-stakes brand and communications decisions
• Produced research briefs and executive presentations translating data into clear strategic direction
• Led internal training on research methodology and applied AI tools

Research on electoral institutions, redistricting, and voting rights — published in peer-reviewed journals and cited before the U.S. Supreme Court.

• Published in PS: Political Science & Politics; cited in Supreme Court amicus brief, Moore v. Harper
• Applied regression analysis, ecological inference, and racially polarized voting methods to redistricting cases
• Research covered by the Washington Post, FiveThirtyEight, and CalMatters