Lead Data Scientist, Personal Loans — ML & Growth

Capital One; New York (NY); On-site; USD 177,000 - 201,000; Full time

Job summary

Capital One is seeking a Principal Associate, Data Scientist for the Personal Loan team in New York. You will build machine learning models on billions of customer records using Python, Spark, and AWS to optimize acquisition, pricing, and verification.

The role partners with data scientists, software engineers, and product managers to translate analytics into business value and drive data-driven decision making at scale.

Qualifications

• Bachelor’s Degree in a quantitative field plus 5 years of data analytics experience
• Master’s Degree in a quantitative field or MBA with a quantitative concentration plus 3 years of data analytics experience
• PhD in a quantitative field (Statistics, Economics, OR...).

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 sets
• Build machine learning models through all development phases: design, training, evaluation, validation, and implementation
• Translate complex work into tangible business goals for stakeholders

Skills

Statistical modeling

Machine learning

Data analysis

Big data processing

Education

Bachelor's degree in a quantitative field (Statistics, Economics, OR etc.)

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

PhD in a quantitative field

Tools

Python

Scala

R

SQL

AWS

Job description

Capital One is seeking a Principal Associate, Data Scientist for the Personal Loan team in New York. You will build machine learning models on billions of customer records using Python, Spark, and AWS to optimize acquisition, pricing, and verification.

The role partners with data scientists, software engineers, and product managers to translate analytics into business value and drive data-driven decision making at scale.