Senior Data Scientist, Credit Risk & BNPL Modeling

PayPal Inc.; Austin (TX); Presencial; USD 131 000 - 194 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Paid time off

Healthcare coverage for you and family

Financial well-being resources

Resumo da oferta

PayPal is seeking an analytical professional to provide second-line oversight of Buy Now Pay Later products, including underwriting and account management practices, ensuring portfolio risk aligns with strategic goals. You will combine credit risk expertise with advanced data science to challenge credit strategies and controls.

In this role, you will lead development of data-driven models, collaborate with global stakeholders, and mentor junior data scientists while ensuring data quality and

Qualificações

• 3+ years relevant experience and a Bachelor's degree OR any equivalent combination of education and experience.
• Advanced degree in a quantitative field (statistics, mathematics, or engineering) preferred.
• Experience in credit risk management or lending and understanding underwriting principles.

Responsabilidades

• Lead development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Ensure data quality and integrity.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.

Conhecimentos

Python

SQL

Credit risk

Data science

Analytics

Formação académica

Bachelor's degree

Advanced degree (preferred)

Descrição da oferta de emprego

PayPal is seeking an analytical professional to provide second-line oversight of Buy Now Pay Later products, including underwriting and account management practices, ensuring portfolio risk aligns with strategic goals. You will combine credit risk expertise with advanced data science to challenge credit strategies and controls.

In this role, you will lead development of data-driven models, collaborate with global stakeholders, and mentor junior data scientists while ensuring data quality and