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Model Risk Manager Jobs in Massapequa, NY (NOW HIRING)

Risk Manager

New York, NY · Hybrid

$150K - $165K/yr

Understanding of risk models and methodologies. Experience with one or more of the following ... A passion for risk management and a proven interest in financial markets through work experience ...

... spend management platform. About the Role The Risk team at Coast owns the full credit and fraud ... Build and maintain dashboards, monitoring alerts, and underlying data models while partnering with ...

Risk Manager

New York, NY · On-site

$95K - $130K/yr

As a Risk Manager, you will report to the VP of Risk and help build Kafene's profit-driven consumer ... modeling to understand root causes and/or potential business opportunities * Translate data into ...

... spend management platform. About the Role The Risk team at Coast owns the full credit and fraud ... Build and maintain dashboards, monitoring alerts, and underlying data models while partnering with ...

Portfolio Risk Manager

Manhattan, NY · On-site

$160K - $190K/yr

Portfolio Risk Manager Corporate Title : Vice President Department : Risk Location: New York The ... Power BI) requiring advanced data handling and analysis, while utilizing Machine Learning models ...

Showing results 41-60

Model Risk Manager information

See Massapequa, NY salary details

$52.8K

$114.4K

$174.4K

How much do model risk manager jobs pay per year?

As of Aug 20, 2026, the average yearly pay for model risk manager in Massapequa, NY is $114,445.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,300.00 and $132,300.00 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.

What are popular job titles related to Model Risk Manager jobs in Massapequa, NY?

For Model Risk Manager jobs in Massapequa, NY, the most frequently searched job titles are:

What job categories do people searching Model Risk Manager jobs in Massapequa, NY look for?

The top searched job categories for Model Risk Manager jobs in Massapequa, NY are:

What cities near Massapequa, NY are hiring for Model Risk Manager jobs?

Cities near Massapequa, NY with the most Model Risk Manager job openings:

Infographic showing various Model Risk Manager job openings in Massapequa, NY as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,445 per year, or $55 per hour.

Manager, Quantitative Analysis - Model Risk Office

Hobbsnews

Manhattan, NY • On-site

$215.20 - $245.60/hr

Other

Posted 2 days ago

New


Job description

Manager, Quantitative Analysis - Model Risk Office

At Capital One 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 Quantitative Analyst 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 cloud 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.

Capital One is selectively recruiting for a Manager for a Model Validation team. The individual would report to the Model Risk Office and work closely with the business groups. This individual, along with their peers, would be responsible for ensuring the accuracy and robustness of the firm’s market risk models. Clients of the group include senior management, business leads, internal audit, and the regulators.

This position is responsible for validating models, specifically those used for derivative pricing and risk management, including derivative valuation, market risk, and counterparty risk models. Strong communication skills are essential to effectively engage with a diverse group of stakeholders, irrespective of their technical background.

Responsibilities
  • Remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
  • Develop model approaches to assess model design and advance future capabilities
  • Understand relevant business processes and portfolios associated with model use
  • Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities
  • Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non‑specialist audiences and senior management
  • Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices
  • Develop and maintain high quality and transparent documentation
  • Leverage the latest open source technologies and tools to identify areas of opportunity in our existing framework

Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation.

Successful candidates will possess
  • Demonstrated track‑record in modeling and experience utilizing model estimation tools such as Python or R
  • Ability to clearly communicate modeling results to management, model risk office, regulator and other modelers
  • Drive to continuously improve all aspects of their work in a collaborative fashion
  • Experience in machine learning
  • Strong communication skills with the ability to quickly understand existing models and new requirements/business needs
  • Experience working with Agile development methodologies
  • Strong grasp of econometric theory and methodologies
  • Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools
  • Experience working with CCAR regulatory requirements
  • Experience with derivative modeling
Basic Qualifications
  • Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date:
    • 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 4 years of experience in quantitative analytics
    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience in quantitative analytics
  • At least 4 years of experience in each of the following skills through education or experience:
    • Statistical or econometric modeling
    • Linear and logistic regression
    • Programming in R, Python, or SQL
    • Presenting statistical concepts and research results to non‑statistical audience
  • At least 4 years of experience in at least 3 of the following skills:
    • Survival analysis modeling
    • Time‑series analysis
    • Panel data (longitudinal data or cross‑sectional time‑series data) analysis
    • Cross‑sectional data analysis
    • Machine learning
    • Analysis and management of large datasets (>1M records)
Preferred Qualifications
  • 5 years of experience with Python, R or other statistical analyst software
  • 5 years of experience in statistical modeling or regression analytics or machine learning
  • At least 2 years of experience in derivative modeling (Fixed income, Commodity, FX or CDS)

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

The minimum and maximum full‑time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part‑time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York, NY: $215,200 - $245,600 for Manager, Quantitative Analysis

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.

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. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23‑A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901‑4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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