Senior Data Science Lead, Personal Loans

Capital One; New York (NY); On-site; USD 251,000 - 286,000; Full time

Job summary

Capital One's Senior Manager, Data Science position is part of the Personal Loan division in New York, NY. You will lead the development of predictive models and ML applications to optimize loan acquisition and pricing strategies, working with a cross-functional team of data scientists and engineers.

The role emphasizes hands-on model building, deployment, and communicating insights to business stakeholders, leveraging Python, AWS, Spark, and related tools in a large-scale data environment.

Qualifications

• Bachelor's degree in a quantitative field plus 7 years of data analytics experience
• Master's degree in quantitative field or MBA with quantitative concentration plus 5 years of data analytics experience
• PhD in quantitative field plus 2 years of data analytics experience
• At least 2 years of experience leveraging open source programming languages for large scale data analysis
• At least 2 years of experience working with machine learning
• At least 2 years of experience utilizing relational databases

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights from large data
• Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation
• Translate the complexity of your work into tangible business goals

Skills

Python

Machine learning

Statistical modeling

Data analytics

Big data

Education

Bachelor's degree in a quantitative field

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

PhD in a quantitative field

Tools

AWS

Spark

H2O

Conda

Job description

Capital One's Senior Manager, Data Science position is part of the Personal Loan division in New York, NY. You will lead the development of predictive models and ML applications to optimize loan acquisition and pricing strategies, working with a cross-functional team of data scientists and engineers.

The role emphasizes hands-on model building, deployment, and communicating insights to business stakeholders, leveraging Python, AWS, Spark, and related tools in a large-scale data environment.