Senior Data Science Leader, Cards & Payments

Capital One; McLean (VA); Presencial; USD 230 000 - 262 000; Tempo integral

Resumo da oferta

Capital One is seeking a Senior Manager, Data Science to lead the Business Cards and Payments data initiatives. You will oversee model development, analytical rigor, and collaboration with data scientists, engineers, and product managers to deliver data-driven decisions at scale.

The role requires strong leadership, statistical expertise, and experience with machine learning, relational databases, and a broad tech stack. Compensation includes performance incentives and comprehensive benefits.

Qualificações

• Bachelor’s degree in a quantitative field plus 7 years analytics experience OR Master’s degree/MBA with quantitative focus plus 5 years analytics OR PhD plus 2 years analytics.
• At least 2 years of experience with open source programming languages for large-scale data analysis.
• At least 2 years of experience working with machine learning and relational databases.

Responsabilidades

• Partner with a cross-functional team to deliver a product customers love.
• Leverage a broad stack (Python, Conda, AWS, H2O, Spark) to reveal insights from large datasets.
• Build ML models through all phases from design to implementation.
• Translate complex work into tangible business goals for stakeholders.

Conhecimentos

Statistically-minded

Leadership

Cross-functional collaboration

Communication

Formação académica

Bachelor's degree in a quantitative field

Master's degree in a quantitative field or MBA with a quantitative concentration

PhD in a quantitative field

Ferramentas

Python

AWS

Spark

H2O

Conda

Descrição da oferta de emprego

Capital One is seeking a Senior Manager, Data Science to lead the Business Cards and Payments data initiatives. You will oversee model development, analytical rigor, and collaboration with data scientists, engineers, and product managers to deliver data-driven decisions at scale.

The role requires strong leadership, statistical expertise, and experience with machine learning, relational databases, and a broad tech stack. Compensation includes performance incentives and comprehensive benefits.