PayPal Credit is the simple, flexible credit line built into your PayPal account. The PayPal Credit Risk Organization is responsible for managing the risk throughout the lifecycle of PayPal’s Credit products. This is an exciting, fast-paced organization where the contribution by team members can significantly impact PayPal’s bottom line as well as our customers’ experience. We’re looking for an Analyst to join the team and help in our efforts to manage PayPal Credit risk globally. You will lead the design and execution of safer experiences for our users and will work on the complex task of keeping fraudsters away from PayPal Credit products. If you’re looking to make an impact at the red-hot intersection of ePayments, consumer lending and online risk management, you’re at the right place. This role is with the Fraud Strategy and Analytics team in the PayPal Credit team, responsible for mitigating fraud on PayPal’s global revolving credit products.
Fraud Strategy & Analytics team is responsible for mitigating fraud on PayPal’s installments and revolving products globally.
Primary responsibilities:
- Conceive, design, and monitor fraud risk management strategies to manage fraud losses and improve business profitability for consumer lending products
- Identify opportunities and gaps within the current portfolio of PayPal’s Fraud Risk controls, including continuously evolving fraud trends
- Formulate & propose solutions to ensure optimal balance between user experience, business enablement, operational expense and loss exposure
- Communicate concise and actionable business strategies and present new strategy recommendations to senior management for approval
- Monitor performance of existing & new solutions and optimize to ensure desired results
Education & Required Skills:
- Bachelor’s degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline
- 3-6 years proven credit or fraud risk analytics experience or equivalent experience in analytics focused roles
- Must be an intuitive, organized analytical thinker, with the ability to perform detailed analysis
- Proficiency in SQL and Excel. Proficiency in at least one statistical analysis tool: SAS / R / Python
- Proven experience in handling large datasets and deriving insights using statistical tools and analytic reasoning
- Strong written, oral, and interpersonal skills a must including the ability to explain and/or present analysis
