BNPL Credit Risk Data Science Lead

BAM Ventures; Chicago (IL); Ibrido; USD 161.000 - 239.000; Tempo pieno

Vantaggi offerti da questo lavoro

Hybrid work model

Health insurance

Paid time off

Descrizione del lavoro

PayPal is seeking an experienced Data Scientist/Lead to design and implement credit risk strategies for the BNPL product in Chicago. You will collaborate with product, sales, finance, and engineering to test and monitor risk strategies, ensuring alignment with business goals and regulatory requirements.

You will mentor junior data scientists, develop models and reporting systems, and drive data-driven decision making across teams in a balanced hybrid work environment.

Competenze

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience leading data science projects.
• BNPL or credit risk experience preferred.

Mansioni

• Lead and manage data science projects, ensuring timely delivery and alignment with business goals.
• Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making.
• Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
• Collaborate with cross-functional teams to understand data needs and provide actionable insights.
• Ensure data quality and integrity through regular audits and validation processes.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement.

Conoscenze

Data analysis

Cross-functional collaboration

Mentoring

Regulatory awareness

Formazione

Bachelor’s degree

Strumenti

SQL

Python

Descrizione del lavoro

PayPal is seeking an experienced Data Scientist/Lead to design and implement credit risk strategies for the BNPL product in Chicago. You will collaborate with product, sales, finance, and engineering to test and monitor risk strategies, ensuring alignment with business goals and regulatory requirements.

You will mentor junior data scientists, develop models and reporting systems, and drive data-driven decision making across teams in a balanced hybrid work environment.