Join a dynamic Trust and Safety team focused on identifying and tackling complex challenges to ensure the integrity of our products. This role is ideal for a strategic, big-picture thinker passionate about user protection and fostering a secure online environment. You will collaborate globally and cross-functionally with engineers and product managers to combat abuse and fraud at Google speed, contributing daily to user trust and safety.

In this leadership position, you will guide a high-performing team dedicated to fighting adversarial actors within Google Ads. Leverage your expertise in data science and fraud detection to drive AI transformation, creating scalable solutions against sophisticated threats like malware and cloaking. Your work will involve close collaboration with Ads Safety, AP Engineering, and gTech teams to architect defense-in-depth strategies that optimize user safety while maintaining a smooth advertiser experience.

Direct and mentor a high-performing team of Engineering Analysts, fostering AI transformation, operational excellence, and strategic execution against adversarial fraud.

Partner with Product Management, Engineering, and Legal to build comprehensive defense-in-depth strategies that enhance user safety and fortify the Google Ads ecosystem against emerging threats.

Lead the development of advanced AI-driven enforcement capabilities to proactively combat abuse at scale. Establish robust evaluation frameworks for the AI era, pioneering rigorous measurement methodologies and overseeing programs to train next-generation AI agents/ML models for fraud detection.

Lead investigations into complex Tactics, Techniques, and Procedures (TTPs) to perform actor tracking and disrupt organized fraud rings targeting Google Ads.

Collaborate closely with sales leadership to architect and implement streamlined recovery experiences for advertisers impacted by policy enforcement, effectively balancing user harm with advertiser experience.

A Bachelor’s degree or equivalent practical experience is required.

Demonstrate 7 years of experience in developing technical strategy and executing data-driven solutions, including building and managing multi-tiered policy enforcement systems.

Possess 3 years of experience in people management, with a focus on mentoring analytical and technical teams (e.g., data scientists, engineering analysts) in applied AI.

Exhibit experience in translating data analyses and emerging abuse trends into actionable business strategies for non-technical stakeholders and leadership.

Preferred qualifications include 10 years of experience in technical strategy and executing data-driven solutions at scale, alongside a strong understanding of machine learning lifecycles, human-in-the-loop workflows, precision/recall metrics, and model drift. Excellent communication, problem-solving, and critical thinking skills are essential for navigating an ever-changing environment.