Manager, Quantitative Analysis, Model Risk Audit

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
McLean, VARichmond, VAPlano, TXNew York, NY
Salary
$179,400–$204,700 / yr
Employment
Full-time
Posted
51 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $187k
This role $192k
$149k $222k
below market most similar roles pay here above market

This role pays more than 57% of similar roles. Most pay $158,625–$214,925 — the blue band above. At the midpoint, this role pays about $192k versus about $187k 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 2164 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1129 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Manager, Quantitative Analysis, Model Risk Audit

JOB TITLE: Manager, Quantitative Analysis - Model Risk Audit The Manager, Quantitative Analysis - Model Risk Audit joins the Model Audit team to review models and model risk practices across the enterprise. This role involves connecting dots to raise appropriate model risk issues and providing assurance to the Audit Committee. You will partner cross-functionally with various lines of business to deliver breakthrough analytical solutions and enhance modeling frameworks. Daily responsibilities include applying expertise in econometric, statistical, and machine learning methods to generate critical insights, creating novel analytical solutions for challenging business problems, and maintaining high-quality documentation. Required skills include proficiency in R, Python, and SQL, along with experience in linear and logistic regression, survival analysis, time-series analysis, and panel data models. You will utilize these tools to solve complex financial institution problems and improve process efficiencies.

What you'll do

  • Apply econometric, statistical, and machine learning methods to generate business insights and decision frameworks.
  • Review models and model risk practices across the enterprise to identify and raise risk issues.
  • Develop novel analytical solutions to solve challenging business problems across different Capital One entities.
  • Identify opportunities to apply automation and quantitative methods to improve process efficiencies.
  • Build cloud-based solutions grounded in data within a cross-disciplinary team.
  • Develop and maintain high-quality, transparent documentation for all models and analytical frameworks.
  • Communicate complex technical subject matter and modeling results clearly to non-technical audiences.

What we're looking for

  • Must have a Master’s degree in a quantitative field plus 4 years of experience in quantitative analytics.
  • Must have a PhD in a quantitative field plus 1 year of experience in quantitative analytics.
  • Must have at least 4 years of experience in statistical or econometric modeling.
  • Must have at least 4 years of experience in linear and logistic regression.
  • Must have at least 4 years of experience in programming using R, Python, or SQL.
  • Must have at least 4 years of experience in presenting statistical concepts and research results to non-statistical audiences.
  • Must have at least 4 years of experience in at least 3 of the listed skills including survival analysis, time-series, or machine learning.
  • Must have 5 years of experience with Python, R, or other statistical analyst software (preferred).
  • Must have 5 years of experience in statistical modeling or regression analytics or machine learning (preferred).
  • Must have at least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS) (preferred).

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