Manager, Data Science, Model Risk Office

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: McLean, VARiverwoods, IL
Salary: $197,300–$225,100 / yr
Posted: 113 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $211k

$155k most similar roles pay here $255k

This role pays more than 62% of similar roles. Most pay $169,425–$245,000 — the shaded band above. At the midpoint, this role pays about $211k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Science, Model Risk Office

Role Posting Log in to save

Manager, Data Science - Model Risk Office joins the Model Risk Office team to perform independent validations of payment network business models. This role focuses on validating fraud risk, Anti-Money Laundering (AML), Counterparty risk, and financial models in accordance with regulatory guidance and internal policies. The successful candidate will evaluate rule-based systems, statistical models, and machine learning approaches such as Gradient Boosting and Random Forest. Day-to-day responsibilities include identifying technical issues in econometric and statistical modeling, maintaining model accuracy through best practices, and creating high-quality documentation for diverse stakeholders. Required skills include proficiency in open-source programming languages, cloud computing platforms like AWS, and experience with Python, Scala, or R. The role addresses critical payment network risks by ensuring the integrity of complex models used to manage financial risk and regulatory compliance.

Skills

Machine Learning Python Scala R AWS Relational Databases Gradient Boosting Deep Learning Clustering Classification Sentiment Analysis Big Data Statistical Modeling econometric, s open-source tools

What you'll do

Perform independent validations of payment network models including fraud, AML, counterparty risk, and financial models.
Validate rule-based systems, statistical models, and machine learning models like Gradient Boosting and Random Forest.
Assess model risks and opportunities by applying expertise in econometric, statistical, and machine learning techniques.
Communicate complex technical concepts and research results clearly to non-specialist audiences and senior management.
Maintain model accuracy and efficiency through continuous improvement and the application of best practices.
Develop and maintain high-quality, transparent documentation for all validated models.
Utilize open-source technologies and tools to identify opportunities within existing frameworks.

What we're looking for

A Bachelor's degree in a quantitative field plus 6 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of experience performing data analytics.
A PhD in a quantitative field plus 1 year of experience performing data 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.
At least 4 years of experience in Python, Scala, or R for large scale data analysis.
At least 4 years of experience with machine learning.

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