Visa Inc. is a global payments technology company that connects consumers, businesses, financial institutions and governments in more than 200 countries and territories, enabling them to use digital currency instead of cash and checks.

Visa does not issue cards, extend credit or set rates and fees for consumers. Visa’s innovations enable its bank customers to offer consumers choices: Pay now with debit, ahead of time with prepaid or later with credit products. From the world’s major cities to remote areas without banks, people are increasingly relying on digital currency along with mobile technology to use their money anytime, make purchases online, transfer funds and access basic financial services. All of which makes their lives easier and helps grow economies.

Behind the Visa brand are our talented employees who continuously raise the bar with innovative solutions and products that deliver the convenience and security of digital currency to more people all over the world.

The candidate will identify fraud patterns and develop risk mitigation processes within Visa’s Digital Developed Markets Business Operations team, while partnering with Product and Analytics teams to develop optimal solution for maximum automation of fraud detection activities.

Responsibilities are focused on building fraud detection strategies and models to mitigate online shopping risk, performed data analysis to identify fraudulent schemes and attacks to protect consumers, merchants, and financial partners.

• Bachelor degree in Math, Statistics, Operations Research or related fields; Master’s degree a plus
• 8+ years fraud and risk management experience in e-/m-commerce risk management with traditional and alternative payment methods
• Extensive knowledge in card-not-present fraud schemes, its risk prevention methods and detection tools for digital, virtual and physical goods
• Experience mitigating online and cyber fraud, such as account takeover, identity spoofing, phishing, online card testing, etc
• Strong quantitative analytical experience, including background with statistical modeling & analysis
  Experience in fraud detection models, cluster analysis, neural networks, decision trees, and similar methodology for detecting and preventing online fraud
• Experience in analyzing fraud patterns, develop empirical rules and prevention strategy to identify and mitigate fraud attacks
• Strong understanding of the online payments landscape across all participants – issuer, merchant, acquirer and network
• Advanced skills in SAS Enterprise Guide/Miner, SQL, Hadoop, and Excel
• Proficient with MS Access, PowerPoint & Office
• Ability to synthesize information and make clear, concise recommendations on a course of action
  

All your information will be kept confidential according to EEO guidelines.