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Model Risk Manager Jobs in Burlington, NJ (NOW HIRING)

NRG Energy

Senior Director, Market Risk

Princeton, NJ · On-site

... model oversight, stress testing, and executive reporting to support informed decision-making across NRG's commercial and risk management activities. The leader serves as a strategic partner to senior ...

NRG

Senior Director, Market Risk

Princeton, NJ · On-site

... model oversight, stress testing, and executive reporting to support informed decision-making across NRG's commercial and risk management activities. The leader serves as a strategic partner to senior ...

AIG

Catastrophe Research Manager

Philadelphia, PA · On-site

$120K - $150K/yr

Catastrophe Research Manager Join us as a Catastrophe Research Manager to take your career to the ... Define and implement the AIG View of Risk * Validate new and existing vendor models * Propose ...

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All JobsModel Risk JobsModel Risk Manager JobsModel Risk Manager Jobs in Burlington, NJ

Model Risk Manager information

See Burlington, NJ salary details

$50.4K

$109.1K

$166.2K

How much do model risk manager jobs pay per year?

As of Jul 13, 2026, the average yearly pay for model risk manager in Burlington, NJ is $109,087.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $126,100.00 per year, depending on experience, location, and employer.

What are some 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 the key skills and qualifications needed to thrive as a Model Risk Manager, and why are they important?

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 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 cities near Burlington, NJ are hiring for Model Risk Manager jobs? Cities near Burlington, NJ with the most Model Risk Manager job openings:
Model Risk Manager jobs near you
Global Head of Catastrophe Risk Analytics

Global Head of Catastrophe Risk Analytics

Starr Insurance Companies

Philadelphia, PA

Full-time

Posted 6 days ago

Job description

Join Starr, a global leader in commercial insurance with over a century of expertise. We empower our employees to innovate, make impactful decisions, and build lasting client relationships worldwide. At Starr, you'll work in an entrepreneurial culture alongside accessible leaders, leveraging our financial strength and vast industry experience to deliver solutions for our clients, no matter how complex. Grow your career with a rapidly growing company that invests in its people and their ability to drive real progress.

The Group Head of Catastrophe Risk Analytics is responsible for leading Catastrophe risk analytics activities across all of Starr Group. This critical leadership position acts as a thought leader and strategic partner, ensuring world-class approaches to catastrophe risk modeling, Risk Analytics, and helps build portfolio management framework that is aligned with underwriting and enterprise risk management strategies. The ideal candidate has deep expertise in catastrophe modeling, a strong analytical mindset, exceptional communication skills, and proven leadership experience.

Key Responsibilities:

  • Develop and execute the group-wide catastrophe risk analytics vision and strategy, ensuring alignment with underwriting strategy, corporate risk appetite and regulatory requirements.
  • Collaborate with underwriting, claims, actuarial, finance, and IT functions to deliver robust catastrophe risk insights that inform technical pricing, portfolio optimization, accumulation control, and capital management.
  • Lead group wide efforts to aggregate catastrophe risk, and deliver associated analytics that support development and execution of underwriting strategy
  • Lead, inspire, and mentor a team of analytics professionals, promoting collaboration, technical excellence, and innovation.
  • Evaluate emerging risks, trends, and technologies in catastrophe modeling and analytics, recommending adoption where appropriate.
  • Oversee the assessment of emerging risks (e.g., climate change, new perils) and evaluate/implement state-of-the-art analytics technology and innovation.
  • Partner with external vendors, data providers, and internal technology partners to develop and deploy optimized Catastrophe modeling workflows and toolset for production of risk analytics.

Qualifications:

  • Advanced degree in a relevant field (e.g., Actuarial Science, Statistics, Geophysics, Engineering, Applied Mathematics, or similar).
  • A minimum of 15 years' experience in catastrophe risk analytics, with significant exposure to both insurance and reinsurance business models.
  • Demonstrated experience in embedding advanced analytics and automation in catastrophe risk management processes.
  • In-depth understanding of capital modeling, risk appetites, reinsurance structures, and portfolio optimization.
  • Strong leadership and people management track record, including in diverse, global, matrixed organizations.
  • Deep expertise in utilization of vendor catastrophe models (RMS, AIR) for development of risk analytics.
  • Excellent interpersonal and communication skills; able to translate complex analytics into actionable business insights.
  • Hands-on experience with advanced analytics, statistical modeling, data governance, big data platforms and visualization tools.
  • Up-to-date knowledge of regulatory environments affecting catastrophe risk.
  • Strong programming and data science skills (e.g., Python, R, SQL).

Starr is an equal opportunity employer, which means we'll consider all suitably qualified applicants regardless of gender identity or expression, ethnic origin, nationality, religion or beliefs, age, sexual orientation, disability status or any other protected characteristic. We recruit and develop our people based on merit and we're committed to creating an inclusive environment for all employees. We offer first class training and development opportunities to all employees. Our aim is to grow our own talent and bring out the best in people.

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