Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.
As an Associate Principal Analyst in the Scams and Verification team, you will be responsible for protecting users from offline scams, scams which take place outside the Google Ads Platform. You will use data to provide recommendations to products and devise solutions (global and hyperlocal) to stay ahead of the fraudsters. You will also be responsible for ensuring good advertisers are provided the right opportunity to serve. You will use applied AI, machine learning, or other techniques to optimize human review cost and efficiency while continuously identifying enforcement gaps and automation opportunities. You will collaborate with cross-functional teams to achieve your business goals and lead projects end-to-end. You will collaborate closely with engineers to develop algorithms and solve quality issues end-to-end. You will problem-solve issues and communicate your findings with others.
At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.
The US base salary range for this full-time position is $142,000-$205,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Collaborate with cross-functional groups such as product manager, engineering, sales, and legal to drive projects that increase users safety and provide better online experience through Google Ads.
- Apply advanced statistical methods and technical analysis to uncover sophisticated abuse vectors. Lead in-depth search investigations into complex tactics, techniques, and procedures to perform actor tracking and disrupt organized fraud rings focusing on Google Ads
- Identify automation and efficiency opportunities and drive solutions through analysis or cross-functional partnerships.
- Analyze massive datasets to identify anomalies and build predictive visual models that influence the evolution of automated detection systems.
- Provide periodic on-call coverage and drive the rapid response for high-severity adversarial incidents, conduct thorough root cause analyses to implement long-term structural preventions. Work with sensitive content or situations and may be exposed to graphic, controversial, or upsetting topics or content.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 7 years of experience in data analytics, Trust and Safety, policy, cybersecurity, or related fields.
Preferred qualifications:
- Master's degree or PhD.
- Experience with machine learning.
- Experience in SQL, building dashboards, data collection/transformation, visualization/dashboards, or experience in a scripting/programming language (e.g., Python).
- Excellent written and verbal communication and presentation skills, with the ability to influence cross-functionally at various levels.
- Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.