Lead Data Scientist – Model Risk & Audit

Capital One; Charlotte (NC); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a Manager, Data Scientist – Model Risk Audit to lead audits of ML models and risk practices across the enterprise. You’ll partner with data scientists, software engineers and product managers to translate complex analyses into business outcomes, leveraging NLP and Generative AI to drive next-generation risk insights.

You’ll work in a fast-paced environment at the intersection of data science and risk governance, with opportunities to influence strategy, mentor others and

Qualifications

• Bachelor's degree in statistics, economics, OR related quantitative field plus 6 years analytics experience.
• Master's degree (or MBA with quantitative focus) plus 4 years analytics experience.
• PhD in quantitative field plus 1 year analytics experience.
• At least 1 year experience with open source languages for large-scale data analysis.
• At least 1 year experience with machine learning.
• At least 1 year experience utilizing relational databases.

Responsibilities

• Partner with cross-functional team to deliver analytics products customers love.
• Audit ML models through all phases from design to implementation.
• Translate complex analyses into tangible business goals.

Skills

Statistics

Machine learning

Open-source languages

Relational databases

Data analysis

Communication

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

Scala

R

SQL

AWS

H2O

Spark

Job description

Capital One is seeking a Manager, Data Scientist – Model Risk Audit to lead audits of ML models and risk practices across the enterprise. You’ll partner with data scientists, software engineers and product managers to translate complex analyses into business outcomes, leveraging NLP and Generative AI to drive next-generation risk insights.

You’ll work in a fast-paced environment at the intersection of data science and risk governance, with opportunities to influence strategy, mentor others and