Promote user trust and safety by managing and mitigating payment fraud and abuse for Google products and services.
Investigate fraud and abuse incidents, identify patterns and trends in order to generate risk management solutions.
Perform statistical analysis using payments and risk data warehouse, collaborate with Engineering and Product teams to create and enhance tools, develop signals, improve system functionality, accuracy and efficiency.
Perform end-to-end assessment of the riskiness and vulnerability of products and features, design and implement fraud and abuse mitigation strategies.
Engage and collaborate with cross-functional teams globally, work closely with Engineers, Product Managers, and various internal and external stakeholders to launch risk mitigation solutions.
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 managing projects and defining project scope, goals, and deliverables.
Preferred qualifications:
Master's degree in a quantitative discipline.
4 years of experience in the payments industry, working in risk or fraud management.
2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
2 years of experience with machine learning systems.
Knowledge of one or more of the following areas: statistical analysis and Machine Learning libraries (e.g., R, Scikit-learn), programming languages (e.g., Python, C/C++), Large Language Models (LLMs) or Generative AI.
Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
