Research Scientist

Matthew Nelson, PhD

I design research and turn complex data into clear, decision-ready insight. My work spans corporate reputation and political science.

View work Download CV
AmazonReputation research across Retail and AWS, in global markets
PhD, USCElectoral institutions, redistricting and voting rights
Peer-reviewedPublished in PS: Political Science & Politics
U.S. Supreme CourtResearch cited by counsel in Moore v. Harper

01Experience

Work

Research spanning corporate reputation and political science. Rigorous methods, clear answers.

Amazon

Research Scientist

June 2025 – Present

Reputation research for Amazon's Reputation Marketing & Insights team, covering Amazon Retail and AWS across global markets.

  • Conduct global survey research and advanced analytics across Amazon Retail and AWS, measuring brand reputation, executive favorability, competitive positioning, and perceptions of Amazon as an AI leader
  • Develop methodology across countries: sampling plans, quota frameworks, questionnaire design, fieldwork specifications, and weighting to census benchmarks to ensure comparable results across markets and over time
  • Model reputation outcomes using logistic regression, Shapley decomposition, and specification curve analysis to identify drivers of brand perception
  • Build research infrastructure: automated Python pipelines and dashboards that turn raw fieldwork into crosstabs and tracking views, plus an internal report-writing tool built on the Claude API with custom steering files for drafting briefs and number checking
  • Interview research and engineering candidates; mentor and evaluate a research scientist intern
Survey designSampling & weightingLogistic regression Shapley decompositionSpecification curvePython pipelines Claude API

Purple Strategies

Research Manager & Quantitative Research Specialist

2023 – 2025

Quantitative research for Fortune 50 companies navigating reputation risk, competitive pressure, and crisis communications. Isolate what drives a reputation, then test which messages move it.

  • Designed survey instruments and statistical models for Fortune 50 clients across energy, pharmaceuticals, consumer products, manufacturing, and technology
  • Modeled reputation drivers with logistic regression and built a driver analysis mapping each attribute by its predictive strength and association with the brand
  • Ran multi-wave message and creative testing across distinct stakeholder audiences, combining max-diff with dial-tested focus groups
  • Produced research briefs and executive presentations translating quantitative findings into strategic recommendations
  • Led firm-wide training on quantitative methods and AI tooling, and helped develop the AI policy governing data safety and researcher accountability
Driver analysisMax-diffMessage testing Dial-tested focus groupsMulti-wave trackingExecutive briefing

USC / Schwarzenegger Institute

Doctoral Researcher & Research Fellow

2018 – 2022

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 help guide redistricting in Riverside County
  • Research covered by the Washington Post, FiveThirtyEight, and CalMatters
Ecological inferenceRacially polarized votingRedistricting analysis Panel regressionExpert reporting

02Publications

Research

Peer-reviewed work and applied policy research at the intersection of electoral institutions, voting rights, and quantitative methodology.

PS: Political Science & Politics  ·  2023  ·  Peer-reviewed

Independent Redistricting Commissions Are Associated with More Competitive Elections

Cited in U.S. Supreme Court amicus brief, Moore v. Harper

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County of Riverside  ·  2021  ·  Expert report

Racially Polarized Voting in Riverside County

Ecological inference and regression analysis for redistricting

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USC Schwarzenegger Institute  ·  2019  ·  Policy report

The Worst Partisan Gerrymanders in U.S. State Legislatures

Washington Post, FiveThirtyEight, CalMatters

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U.S. Supreme Court  ·  2022  ·  Amicus brief (cited)

Schwarzenegger Amicus Brief — Moore v. Harper, No. 21-1271

Research cited by counsel before the U.S. Supreme Court

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03Built

Projects

One side project, built end to end: the game, the art pipeline behind it, and the test suite that keeps it honest.

On the web and the App Store · Free · Nothing collected

Bouncy Doggo

One golden retriever, six games. Three to bounce: climb from a meadow to a rainbow summit, hop through a garden of shrine gates, and cross a toy town before the bath catches up. Three to think: count the crowd, find the pairs, spot the odd pup out. Every game pays bones, and the bones dress the dog from a wardrobe of 150 coats, hats, eyewear, capes, shoes and auras. The art is modeled and lit in Blender, baked to sprites and composited on a hand-drawn canvas, and the whole thing ships as one file that runs byte-identical in the browser and inside the iOS app.

1 fileweb and iOS, byte for byte the same
150wardrobe items on six racks, from coats to auras
6games: three to bounce, three to think
72bugs planted on purpose to prove the tests bite
Play it How it is made App Store
Bouncy Doggo: the game modes, six picture cards, the bounce games above the brain games

04Curriculum Vitae

CV

Full CV covering research experience, publications, and methods. Read it in the browser, or take the one-page PDF.

Read CV Download PDF