Sr. Quantitative Model Analyst

Fhlbcin

Cincinnati (OH)

On-site

USD 120,000 - 160,000

Full time

14 days+
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Job summary

FHLB Cincinnati seeks a Sr. Quantitative Model Analyst to independently validate and monitor bank models used in pricing, risk measurement, and decision making. You will ensure regulatory compliance and contribute to governance and risk frameworks across the organization.

You will lead validation efforts, collaborate with stakeholders, and mentor team members while staying current with industry best practices and technology trends in model risk management.

Qualifications

  • Master’s Degree in finance, economics, mathematics, statistics, or financial engineering (PhD a plus).
  • At least seven years’ experience in model validation and/or model development at financial institutions, rating agencies, or regulatory bodies.
  • Proficiency in Python, R, MATLAB with data manipulation and statistical analysis; strong Excel/Word skills; awareness of model risk standards.

Responsibilities

  • Lead and perform model validation and governance activities for Bank models; assess accuracy, reliability, and robustness.
  • Contribute to model risk management framework, policy, and change management processes.
  • Prepare comprehensive validation reports with findings and recommendations; communicate results to technical and non-technical audiences.
  • Mentor junior staff and collaborate with stakeholders to strengthen the bank's model risk environment.

Skills

Analytical thinking
Communication skills
Team collaboration
Detail orientation

Education

Master’s Degree in finance, economics, mathematics, statistics or financial engineering

Tools

Python
R
MATLAB
Excel
Word

Job description

Sr. Quantitative Model Analyst

General Summary: Independently leads and assists activities related to managing and mitigating model risks, by independently performing validations, monitoring governance, and providing guidance and expertise related to models used by the Bank. The Senior Analyst collaborates with various stakeholders to ensure the accuracy, reliability, and regulatory compliance of models used for pricing, risk measurement, and decision‑making processes.

Principal Duties and Responsibilities
  • 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

Flexibility to work outside normal business hours if required to complete time‑sensitive projects. Requires close attention to detail to ensure the accuracy and integrity of information supplied to senior management and members.

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