Engineering Analyst, Payments Trust and Safety

Trust and 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, problem-solving skills, user insights, and proactive communication to protect users and partners from abuse across Google products such as Play, Cloud, Pay, YouTube, Shopping, Fi.

In this role, you are a big-picture thinker and strategic team-player, passionate about doing what’s right. You work globally and cross-functionally with Google engineers and product managers identifying and fighting abuse and fraud cases at Google speed - with urgency. You take pride in knowing that every day you are working hard to promote users’ trust in Google and ensuring the highest levels of user safety.

You will be responsible for restricting or preventing fraudsters and abusers to ensure a safe and secure payments environment for our users. You are keen to identify and solve complex problems and have very strong problem-solving and technical skills to innovate and optimize our processes and tools. You are proactive, motivated, organized, responsible, innovative and are able to work well in a fast-paced, global, cross-functional, and team-oriented environment and demonstrate very strong technical know-how, effective communication to get things done. You will also work with product and engineering teams to make sure that new products and features provide a good, safe experience for users.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $132000 - $190000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
  
• 2 years of experience in the Payments industry, working on risk or fraud management.
• 2 years of experience managing projects and defining project scope, goals, and deliverables.
  

Preferred qualifications:

• Master's degree in a quantitative discipline.
  
• Working knowledge in one or more of the following areas: programming languages (e.g., Python, R, C/C++), statistical analysis (e.g., Scipy) and machine learning libraries (e.g., Scikit-learn, TF), Large Language Models (LLMs) or Generative AI Agents.
• Demonstrated ability to identify workflow pain points, optimize, automate and scale processes.
• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
• Strong project and program management skills and experience.