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Quantitative Risk Manager Jobs in Ohio (NOW HIRING)

US Bank

Quantitative Model Analyst 2

Cincinnati, OH · On-site

Our team is seeking a strong, decisive, results-oriented quantitative analyst who will be ... risk management approaches - Advanced understanding of applicable regulatory rules, guidance, or ...

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$49K

$106.1K

$161.6K

How much do quantitative risk manager jobs pay per year?

As of Jul 8, 2026, the average yearly pay for quantitative risk manager in Ohio is $106,056.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,600.00 and $122,600.00 per year, depending on experience, location, and employer.

What can I do with a quantitative risk management degree?

A degree in quantitative risk management prepares individuals for roles such as risk analyst, risk manager, or quantitative analyst in finance, insurance, or consulting firms. These roles involve assessing and modeling financial risks using statistical tools, programming languages like Python or R, and risk management frameworks. Professionals in this field often work with regulatory compliance and may pursue certifications like FRM or PRM.

What is the salary of a quant risk manager?

A quantitative risk manager's salary typically ranges from $100,000 to $200,000 annually, with higher compensation often associated with experience, advanced degrees, and certifications such as FRM or CFA. In addition to base salary, bonuses and performance incentives can significantly increase total compensation in this role.

What does a quantitative risk manager do?

A quantitative risk manager analyzes financial data and models to identify, measure, and manage risks within an organization. They use statistical techniques, programming skills, and risk management tools to develop strategies that minimize potential losses and ensure regulatory compliance.

How does a Quantitative Risk Manager typically collaborate with other departments within a financial institution?

Quantitative Risk Managers work closely with teams such as trading, compliance, IT, and senior management to identify, measure, and mitigate financial risks. They often translate complex quantitative models into actionable insights for non-technical stakeholders and facilitate the integration of risk metrics into daily decision-making processes. Collaboration is essential for ensuring that risk assessments align with business objectives and regulatory requirements, often requiring regular cross-functional meetings and clear communication.

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

To thrive as a Quantitative Risk Manager, you need strong analytical abilities, a deep understanding of statistics and financial mathematics, and typically an advanced degree in finance, mathematics, or a related field. Proficiency in programming languages like Python or R, experience with risk modeling software, and certifications such as FRM or CFA are highly valuable. Exceptional problem-solving, communication, and collaboration skills help you convey complex risk metrics to stakeholders and work effectively in cross-functional teams. These skills ensure accurate risk assessments, regulatory compliance, and informed decision-making in dynamic financial environments.

How much do quant risk managers make?

Quantitative risk managers typically earn between $100,000 and $200,000 annually, with senior roles and those in major financial centers earning higher salaries. Compensation often includes bonuses and benefits, and strong skills in mathematics, programming, and risk modeling are essential for higher-paying positions.

What is a Quantitative Risk Manager?

A Quantitative Risk Manager is a professional who uses mathematical models, statistical analysis, and quantitative techniques to identify, measure, and manage financial risks within an organization. They often work in banks, investment firms, or insurance companies to analyze market, credit, and operational risks. Their responsibilities include developing risk models, monitoring risk exposures, and advising senior management on risk mitigation strategies. They play a key role in ensuring that organizations make informed decisions and comply with regulatory requirements.

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

AspectQuantitative Risk ManagerQuantitative Analyst
Primary FocusAssessing and managing risk exposure across financial portfoliosDeveloping models and algorithms for investment strategies
Required CredentialsAdvanced degrees in finance, mathematics, or related fields; certifications like FRM or CFADegrees in finance, mathematics, or statistics; often pursuing CFA or similar
Work EnvironmentFinancial institutions, risk management departmentsInvestment firms, hedge funds, banks
Key SkillsRisk assessment, regulatory knowledge, quantitative modelingData analysis, programming, financial modeling

While both roles involve quantitative skills and financial knowledge, Quantitative Risk Managers focus on identifying and mitigating risks within organizations, whereas Quantitative Analysts primarily develop models to inform investment decisions. Understanding these differences helps professionals choose the right career path or job search focus.

What are popular job titles related to Quantitative Risk Manager jobs in Ohio? For Quantitative Risk Manager jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Manager jobs in Ohio look for? The top searched job categories for Quantitative Risk Manager jobs in Ohio are:
What cities in Ohio are hiring for Quantitative Risk Manager jobs? Cities in Ohio with the most Quantitative Risk Manager job openings:
Quantitative Risk Manager jobs near you

Sr. Quantitative Model Analyst

Federal Home Loan Bank Cincinnati

Cincinnati, OH • On-site

Full-time

Posted yesterday

Job description

Sr. Quantitative Model Analyst
General Summary:
Independentlyleads and assists activities related to managing and mitigating model risks, byindependently performing validations, monitoring governance, and providingguidance and expertise related to models used by the Bank. The Senior Analystcollaborates with various stakeholders to ensure the accuracy, reliability, andregulatory compliance of models used for pricing, risk measurement, anddecision-making processes.
Principal Duties andResponsibilities:
  • Model Validation and Governance: Independently perform validation and governance efforts related to Bank models. Conduct comprehensive assessments of model accuracy, reliability, and robustness. Independently perform model validation activities, including reviewing model assumptions, methodologies, and implementation. Identify limitations, weaknesses, or gaps in models and propose enhancements or alternative approaches.
  • Model Risk Management Framework: Contribute to the development and enhancement of the bank's model risk management framework, policies, and procedures. Support the implementation and management of model risk management processes, including model inventory, model change management, and ongoing model monitoring.
  • Regulatory Compliance: Coordinate with key stakeholders to ensure compliance with regulatory model risk requirements (FHFA AB 2013-07; FHFA AB 2022-03).
  • Risk Identification and Measurement: Identify and assess the risks associated with financial models, including model errors, biases, and limitations.
  • Model Documentation and Reporting: Prepare comprehensive model validation reports, documenting the validation process, findings, and recommendations.
  • Collaboration and Leadership: Collaborate with key stakeholders to provide guidance and expertise in support of a sound model risk management environment at the Bank. Provide guidance and mentorship to junior members of the model risk management team.
  • Continuous Improvement and Innovation: Stay abreast of emerging trends, industry best practices, and technological advancements in model risk management. Identify opportunities for process optimization, automation, and efficiency gains within the model risk management function and ERM department.
  • Performs additional duties as requested by management.

Minimum Knowledge,Skills and Abilities Required:
  • Knowledge at a level normally acquired through the completion of a Master's Degree in finance, economics, mathematics, statistics, or financial engineering or equivalent work experience with financial, statistical, market risk, or credit risk models. A Ph.D. in a relevant discipline is a plus.
  • At least seven years' experience in model validation and/or model development at a financial institution, rating agency, regulatory agency, or as a financial industry consultant.
  • Strong understanding of financial models and their application in areas such as pricing, risk measurement, and decision-making. Knowledge of various model types, including credit risk, market risk, and liquidity risk models.
  • Knowledge of regulatory guidelines and industry standards for model risk management, such as AB 2013-07, SR 11-7, and OCC Bulletin 2011-12, is highly desirable.
  • Proficiency in programming languages such as Python, R, or MATLAB, with experience in data manipulation, statistical analysis, and model development.
  • Advanced/Intermediate Microsoft Office skills (particularly Excel and Word)
  • Strong analytical and problem-solving skills, with the ability to critically evaluate complex models and identify potential risks.
  • Excellent written and verbal communication skills, with the ability to convey technical concepts and validation results to both technical and non-technical audiences.
  • Detail-oriented with strong organizational skills, able to manage multiple projects simultaneously and meet deadlines.
  • Ability to work collaboratively within a team environment and build effective working relationships with stakeholders at various levels.
  • Demonstrates interest in working with a variety of backgrounds and perspectives that align with the Bank's core value.
  • Promotes an environment of empathy and respect to ensure the inclusion of all team members.

Working Conditions:
Flexibilityto work outside normal business hours if required to complete time sensitiveprojects. Requires close attention to detail to ensure the accuracy andintegrity of information supplied to senior management and members.

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