Iris Gu

Sunnyvale,CA

Summary

3 years of experience at Google specializing in advertising adversarial patterns, driving scalable malware detection systems, model validation, and product strategy to protect the ads ecosystem at global scale.

Overview

years of professional experience

Work History

Engineering Analyst

Google

Sunnyvale, CA

08.2022 - Current

Spearheaded data science initiatives to detect advertising ecosystem abuse, with a technical focus on LP malware, cloaking and deceptive redirects.
Owned model validation for major ML launches (e.g., Malware V4), driving a 78% uplift in threat detection and a 60% reduction in false negatives.
Identified and mapped adversarial TTPs to threat actors, driving a transition from reactive enforcement to proactive, actor-level mitigation and scalable defense strategies
Defined and evolved product KPIs (BCI/GCI) and impact scoring, quantifying business health and guiding product strategy through data-backed insights.
Built and scaled end-to-end tooling, including cloaking evidence dashboards and automated sweeps, reducing manual review time by 18.4% for global teams.
Led data-driven incident response for high-risk abuse events, uncovering systemic vulnerabilities in ads reseller ecosystems and executing cross-functional enforcement.
Partnered with Engineering, Product, and Policy teams to integrate "Safety by Design" principles into the ads roadmap and system architecture.
Delivered continuous threat intelligence and trend analysis to proactively adapt detection strategies against sophisticated adversarial actors on ads.

Data Analyst & Product Strategy

Microsoft (f.k.a Xandr)

New York, NY

04.2020 - 07.2022

Directed analytics and data-driven strategy for core Audience & Identity products, specializing in user identification and cross-device tracking technologies.
Executed end-to-end analytics frameworks for product experimentation, delivering data-driven recommendations that significantly improved product adoption among business clients.
Architected and maintained specialized BI tools and automated dashboards to monitor the health of identity products and visualize critical KPIs for leadership.
Streamlined stakeholder management by delivering technical insights and project milestones to diverse teams including Engineering, Sales, and Executive leadership.

Education

Master of Science - Applied Analytics

Columbia University

New York, NY

12-2019

Bachelor of Commerce - Finance, Minor in Mathematics

University of British Columbia

Vancouver, BC, Canada

05-2018

Skills

Technical: Python, SQL, Statistical Modeling, Data Pipelines
Data Science: Feature Engineering, Model Evaluation (Precision/Recall, FN Reduction), Signal Design

Adversarial Domain: Ads Landing Page Malware, Cloaking, Threat Actor Analysis, TTP Tracking, Abuse Pattern Modeling, Root Cause Analysis
Product Strategy: Metric Definition, Product Roadmap Influence, XFN Stakeholder Management

Timeline