Investigate fraud and abuse incidents, identify patterns and trends in order to generate holistic risk management solutions. Promote user trust and safety by managing and mitigating payment fraud, scams and abuse on Google products and services.
Perform statistical analysis using payments and risk data warehouses. Collaborate with Engineering and Product teams to create and enhance tools, develop signals, improve system functionality, accuracy and efficiency.
Facilitate and manage operations programs, working closely with Google Engineers, Product Managers and vendor operations to develop and track project schedules and timelines. Use technical expertise to drive and implement automation opportunities.
Perform end-to-end assessment of the associated risk and vulnerability of products and features. Respond to escalations from internal and external parties within designated service levels.
Perform on-call responsibilities on a rotating basis, including weekend coverage.
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.
2 years of experience with one or more of the following languages: SQL, R, Python, or C++.
Preferred qualifications:
Master's degree in a quantitative discipline.
2 years of experience in the payments industry, working on risk or fraud management.
Knowledge of one or more of the following areas: statistical analysis and machine learning libraries (e.g., R, Scikit-learn,TensorFlow), programming languages (e.g., Python, C/C++), Large Language Models (LLMs) or Generative AI.
Ability to identify workflow pain points, optimize, automate and scale processes.
Ability to be comfortable interacting with internal and external stakeholders.
Excellent communication, problem-solving, and critical thinking skills with attention to detail in an ever-changing environment.
