Sr Data Scientist, BNPL Credit Risk Oversight

PayPal • Austin, TX

3d • $130,500 - $193,600 • Hybrid

About The Position

This role provides analytical support for Second Line oversight of Buy Now Pay Later (BNPL) products, including underwriting and account management practices. The position helps ensure the portfolio is properly managed, aligned with strategic goals, and operating within the risk appetite. As part of the Second Line of Defense, the role applies analytical rigor and credit risk expertise to independently oversee credit strategy and risk controls and deliver effective challenges.

The role leads the development and implementation of advanced data science models and algorithms, works with stakeholders to understand requirements and deliver solutions, drives data science best practices, and ensures data quality. It also mentors junior data scientists and stays current with developments in data science. Responsibilities include assessing credit strategies and exposure limits or thresholds for alignment with the Risk Appetite and adherence to changes in the business model or regulatory environment.

PayPal's balanced hybrid work model generally involves three days in the office and two days at either the PayPal office or the employee's home workspace. The role has no expected travel. The listed annual base-pay range is $130,500–$193,600 in Chicago, Illinois, and Austin, Texas; additional compensation may include an annual performance bonus, equity, or other incentives, as applicable.

Requirements

• At least 3 years of relevant experience and a bachelor's degree, or an equivalent combination of education and experience.
• Strong analytical skills, including the ability to work with data, identify patterns, derive and visualize business insights, and translate them into compelling narratives.
• Strong written, verbal, interpersonal, and collaborative communication skills, including the ability to explain credit risk concepts to technical and non-technical audiences and communicate Second Line challenges effectively and respectfully.
• Critical thinking, influencing, negotiation, and relationship-building skills, including the ability to interface internally and externally to achieve high-quality outcomes.
• Ability to work with geographically dispersed teams, including teams abroad and in different time zones.

Nice To Haves

• Advanced degree in a quantitative field such as statistics, mathematics, or engineering.
• At least 3 years of experience in credit risk management or lending, with understanding of credit risk fundamentals such as underwriting principles and credit risk metrics.
• Experience in merchant or small business lending environments.
• Understanding of Second Line of Defense functions.
• Proficiency with Python, SQL, or other statistical analysis tools.

Responsibilities

• Provide analytical support for Second Line oversight of BNPL underwriting and account management practices.
• Help ensure the portfolio is properly managed, aligned with strategic goals, and operating within the risk appetite.
• Provide independent oversight and effective challenges on credit strategy and risk controls.
• Lead the development and implementation of advanced data science models and algorithms.
• Collaborate with stakeholders to understand requirements and deliver solutions.
• Drive best practices in data science.
• Ensure data quality and integrity in all processes.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.
• Assess, review, and analyze current credit strategy and exposure limits or thresholds for alignment with the Risk Appetite.
• Ensure adherence to changes in the business model and regulatory environment.

Benefits

• Comprehensive, choice-based wellbeing programs supporting physical, emotional, and financial wellbeing.
• Generous paid time off.
• Healthcare coverage for employees and their families.
• Resources to support financial security and mental health.
• Annual performance bonus, equity, or other incentive compensation, as applicable.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level