Data Science Manager: US Card Customer Insights

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Manager, Data Science for US Card Customer Management. The role centers on building top-tier ML solutions for real-time customer behavioral prediction and valuation forecasts operating across billions of records.

You will partner with data scientists, engineers, and product managers to deliver customer-loved products, using Python, AWS, Spark, and open-source tools to drive business impact and data-driven decisions.

Qualifications

• Bachelor’s degree in a quantitative field plus 6 years of analytics experience
• Master’s degree in a quantitative field or MBA with quantitative concentration plus 4 years analytics
• PhD in a quantitative field plus 1 year analytics
• At least 1 year of experience leveraging open source programming languages for large scale data analysis
• At least 1 year of experience working with machine learning
• At least 1 year 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 numeric and textual data
• Build machine learning models through all phases of development from design to training, evaluation, validation, and implementation
• Translate the complexity of your work into tangible business goals

Skills

Python

AWS

Spark

H2O

Conda

Relational databases

Machine learning

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

SQL

Job description

Capital One is seeking a Manager, Data Science for US Card Customer Management. The role centers on building top-tier ML solutions for real-time customer behavioral prediction and valuation forecasts operating across billions of records.

You will partner with data scientists, engineers, and product managers to deliver customer-loved products, using Python, AWS, Spark, and open-source tools to drive business impact and data-driven decisions.