Job Description:

PayPal Credit is the simple, flexible credit line built into your PayPal account. PayPal Credit Risk Organization is responsible for managing the risk throughout the lifecycle of PayPal’s global 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.

Fraud Strategy & Analytics team owns fraud losses from PayPal’s installments, lines and partner-credit offerings for PayPal’s global consumers, proposing solutions and measuring effectiveness of solutions post-implementation.

In order to capture all the events critical to detect fraud loss pressure and fraud-driven friction, the analyst must be comfortable with multiple data platforms, be able to combine data at the account, transaction and critical event levels.

The Fraud Strategy & Analytics team has end to end ownership of fraud losses from PayPal’s installments, lines and partner-credit offerings for PayPal’s global consumers, proposing solutions and measuring effectiveness of solutions post-implementation.

Day to day responsibilities include:

• Identifying opportunities and gaps within current portfolio of PayPal’s Fraud Risk controls, including continuously evolving fraud trends

• Working with the product team and establish a feedback loop to provide continuous improvements related input for the Tools and capabilities at various Fraud checkpoints.

• Working closely with partners in Risk Platform, Global Risk and Data Sciences, Operations, Credit Product Management, Legal & Compliance and other teams to align technical solutions with business strategies and/or support several complex business processes

• Provide operational reporting and analysis (Routine and ad hoc) related to SLA and KPI compliance tracking for existing solutions and overall Fraud controls.

•   Own data governance by proactively performing regular audits to identify errors or opportunities and closely monitoring performance of existing and new solutions to ensure expectations are met

• Based on analysis: Identifying trends and formulating a solution to ensure optimal balance between user experience, business enablement, operational expense and loss exposure related to proposed solution.

• Explore on-going optimization opportunities of existing risk solutions

• Closely monitoring performance of existing and new solutions to ensure expectations are met

Job Qualifications

Required Skills: 

• Proficiency in SQL and Excel

• Proficiency in at least one statistical analysis tool: SAS / R / Python

• Strong analytical skills: ability to build quick estimates using back-of-the-envelope analysis, structure (and, if needed, execute) more complex analyses, pull together business cases..  Above all, the job calls for comfort with data – ability to manipulate it, question its validity, interpret it, and develop recommendations based on it

• Ability to manage a large, diverse set of to-do’s – prioritize, stay on top of multiple work streams, monitor progress

• Ability to work with leadership & stakeholders to define project scope and direction, driving large pieces of the work independently

• Strong communication skills – a sense of appropriate communication mechanism/approach to use given context/circumstances. 

• Experience working with cross-functional, geographically distributed teams, managing by influence is a plus.

• Ability to contribute to strategic discussions and represent Risk in cross-functional meetings

• Dedicated, proactive, curious and eager to learn new approaches / methodologies – a must

Desired Skills:

• Must be an intuitive, organized, analytical thinker, with the ability to perform detailed analysis
• Strong written, oral, and interpersonal skills a must, including the ability to explain and/or present analysis
• Must have good business judgment with demonstrated ability to think creatively and strategically
• Aptitude and willingness to roll up the sleeves and get involved in the details
• Risk management / big data manipulation experience is a plus

Education

Bachelor’s degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline

Experience

2 – 4 years related experience

MS/MBA or PhD degree can qualify for some years of experience