Minimum qualifications:

• 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.
  
• Experience with programming languages (e.g., Python, R, Julia) and database languages (e.g., SQL).
  

Preferred qualifications:

• Master’s degree or PhD in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, etc.), or a related field.
  
• 2 years of experience in the Payments industry, working on risk or fraud management.
  
• Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript) or data-focused programming.
  
• 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++), LLMs, or Generative AI.
  
• Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
  
  
  
  Responsibilities
  
  
  • Promote user trust and safety, managing and mitigating payment fraud and abuse for Google products and services. Investigate fraud and abuse incidents and identify patterns and trends to generate risk management solutions.
  • 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.
  • Perform assessment for 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.