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Model Risk Manager Jobs in Vienna, VA (NOW HIRING)

Deloitte

Financial Risk Manager

Mclean, VA · On-site

Financial Services Manager - Financial Risk Our Deloitte Regulatory, Risk & Forensic team helps ... Knowledge of financial services business models, products, and services * Experience in banking ...

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Model Risk Manager information

See Vienna, VA salary details

$51.7K

$112K

$170.6K

How much do model risk manager jobs pay per year?

As of Aug 19, 2026, the average yearly pay for model risk manager in Vienna, VA is $111,969.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,300.00 and $129,500.00 per year, depending on experience, location, and employer.

What does a model risk manager do?

A Model Risk Manager is responsible for identifying, assessing, and mitigating risks associated with financial and analytical models used by an organization. They ensure that models are accurate, reliable, and compliant with regulatory standards by overseeing validation processes and monitoring model performance. Their role often includes collaborating with model developers, conducting independent reviews, and implementing model governance frameworks to minimize potential losses or errors stemming from model misuse or inaccuracies.

What skills and qualifications are needed to be a model risk manager?

To thrive as a Model Risk Manager, you need a solid background in quantitative finance, statistics, or mathematics, often supported by an advanced degree and experience in model development or validation. Familiarity with programming languages such as Python or R, risk management frameworks, and regulatory requirements like SR 11-7 or ECB guidelines is typically expected. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for articulating complex model risks to stakeholders. These competencies are vital for ensuring the accuracy, compliance, and reliability of financial models within an organization.

What are common challenges a model risk manager faces when validating complex financial models?

Model Risk Managers often encounter challenges such as limited or incomplete data, evolving regulatory requirements, and the need to validate highly complex or proprietary models. They must work closely with model developers, quantitative analysts, and compliance teams to ensure all assumptions and methodologies are sound. Staying up to date with industry best practices and maintaining clear documentation are also crucial, as is effectively communicating findings to both technical and non-technical stakeholders.

What is the difference between Model Risk Manager vs Quantitative Analyst?

AspectModel Risk ManagerQuantitative Analyst
Required CredentialsAdvanced degrees in finance, statistics, or mathematics; certifications like FRM or CFADegree in finance, economics, mathematics, or related fields; often CFA or CQF
Work EnvironmentFocus on risk management teams within financial institutions; regulatory complianceAnalytical roles within trading, investment, or banking divisions; model development
Employer & Industry UsageFinancial institutions, banks, asset managersInvestment firms, hedge funds, banks, financial services

The Model Risk Manager primarily oversees and mitigates risks associated with financial models, ensuring compliance and accuracy. In contrast, Quantitative Analysts develop and implement models to support trading, investment, or risk strategies. While both roles require strong quantitative skills and similar credentials, their focus areas differ—risk management versus model development and analysis.

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What job categories do people searching Model Risk Manager jobs in Vienna, VA look for?

The top searched job categories for Model Risk Manager jobs in Vienna, VA are:

What cities near Vienna, VA are hiring for Model Risk Manager jobs?

Cities near Vienna, VA with the most Model Risk Manager job openings:

Model Risk Manager jobs near you
Infographic showing various Model Risk Manager job openings in Vienna, VA as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $111,969 per year, or $53.8 per hour.

Senior Manager, Data Science - Model Risk Office

Capital One National Association

Mclean, VA • On-site

$229.90 - $262.40/hr

Other

Posted yesterday

New

Job description

Senior Manager, Data Science - Model Risk Office

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision‑making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise.

The successful candidate will join the Card Fraud Model Risk team, which is tasked with evaluating risk for Card Fraud models used throughout the customer lifecycle. This role covers fraud detection at various stages, including application, transaction, and payment, for both first‑party and third‑party use cases. The team conducts thorough assessments of existing fraud models and builds independent challenger models to ensure effective oversight.

Working within a small, innovative group, you will act as a key individual contributor investigating advanced algorithms such as graph, neural, tree‑based, and sequence methods to create robust challenger models. Additionally, you will provide mentorship to junior data scientists as you explore cutting‑edge solutions and oversee card fraud model risk.

Role Description
  • 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 the insights hidden within huge volumes of numeric and textual data
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state‑of‑the‑art methods, technologies, and applications and seek out opportunities to apply them.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
  • Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms.
  • Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Basic Qualifications:
  • Currently has, or is in the process of obtaining one of the following:
    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics
    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics
    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis
  • At least 2 years of experience working with machine learning
  • At least 2 years of experience utilizing relational databases
Preferred Qualifications:
  • PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 1 year of experience managing people
  • At least 5 years’ experience in Python, Scala, or R for large scale data analysis
  • At least 5 years’ experience with hands‑on Machine Learning model development and deployment
  • Experience with model development/deployment pipeline (e.g. Kubeflow, Kubernetes) is preferred.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science
New York, NY: $250,800 - $286,200 for Sr Mgr, Data Science
Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science
Riverwoods, IL: $209,000 - $238,500 for Sr Mgr, Data Science

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being. Learn more at the Capital One Careers website. Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days. No agencies please.

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.

To request accommodations, contact RecruitingAccommodation@capitalone.com.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com.

Capital One does not provide, endorse nor guarantee and is not liable for third‑party products, services, educational tools or other information available through this site.

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