Lead Data Science Manager - Card Customer Growth

ITSMF; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Manager of Data Science for US Card Customer Management. The role focuses on building ML solutions for real-time customer behavior prediction and valuation forecasts, collaborating with business, engineers, analysts, data science/quants, and product teams.

The candidate will work with Python, Conda, AWS, H2O, Spark, and other tools, delivering models from design to deployment while aligning with business goals and customer-centric outcomes.

Qualifications

• Bachelor's degree in a quantitative field plus 6 years of data analytics experience
• Master's degree in a quantitative field or MBA with quantitative concentration plus 4 years of data analytics experience
• PhD in a quantitative field plus 1 year of data analytics experience
• At least 1 year of experience leveraging open source 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 cross-functional team to deliver a product customers love
• Leverage Python, Conda, AWS, H2O, Spark to analyze large volumes of data
• Build machine learning models through all development phases
• Translate complex work into tangible business goals

Skills

Statistical modeling

Machine learning

Python

Spark

AWS

H2O

SQL

Data analysis

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

Python

Conda

AWS

H2O

Spark

Job description

Capital One is seeking a Manager of Data Science for US Card Customer Management. The role focuses on building ML solutions for real-time customer behavior prediction and valuation forecasts, collaborating with business, engineers, analysts, data science/quants, and product teams.

The candidate will work with Python, Conda, AWS, H2O, Spark, and other tools, delivering models from design to deployment while aligning with business goals and customer-centric outcomes.