Senior Data Science Leader — Model Risk & Governance

Capital One; Chicago, Northern (IL, KY); Hybrid; USD 209,000 - 239,000; Full time

Benefits offered by this job

Health benefits

Performance-based incentives

Long-term incentives

Job summary

Capital One is seeking a Senior Manager, Data Science to join the Card Model Risk team in Chicago. You will partner with data scientists, software engineers, and product managers to deliver ML products that are governed and aligned with business goals.

You'll use Python, AWS, Spark and related tools to build models from design through training and validation, translating complex analyses into measurable outcomes for risk management and underwriting.

Qualifications

• Bachelor's degree in a quantitative field plus 7 years of data analytics experience.
• Master's degree (or MBA with quantitative concentration) plus 5 years of data analytics.
• PhD in a quantitative field plus 2 years of data analytics experience.
• At least 2 years using open-source programming languages for large-scale data analysis.
• At least 2 years of machine learning experience and relational database expertise.

Responsibilities

• Partner with cross-functional teams to deliver ML products that customers love.
• Leverage Python, AWS, Spark, and related tools to reveal insights from large data sets.
• Build models through design, training, evaluation, validation, and implementation.
• Translate complex analyses into tangible business goals for risk and underwriting.

Skills

Open-source programming

Machine learning techniques

Relational databases

Education

Bachelor's degree in quantitative field

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

PhD in quantitative field

Tools

AWS

Spark

H2O

Job description

Capital One is seeking a Senior Manager, Data Science to join the Card Model Risk team in Chicago. You will partner with data scientists, software engineers, and product managers to deliver ML products that are governed and aligned with business goals.

You'll use Python, AWS, Spark and related tools to build models from design through training and validation, translating complex analyses into measurable outcomes for risk management and underwriting.