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Associate Quantitative Risk Analyst Jobs in Raleigh, NC

Bachelors in a quantitative discipline (Economics, statistics, finance, data science or analytics ... Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR ...

Quantitative Associate

Durham, NC · On-site

$125K - $140K/yr

Analyze and model portfolio exposures, performance, and risk across a diverse range of asset ... for Quantitative Associate. * Exposure to machine learning libraries (e.g., scikit-learn ...

Quantitative Associate

Durham, NC · On-site

$125K - $140K/yr

Analyze and model portfolio exposures, performance, and risk across a diverse range of asset ... for Quantitative Associate. * Exposure to machine learning libraries (e.g., scikit-learn ...

Investigate and analyze potential and actual professional liability and general liability exposures ... A Bachelor's degree in a clinical field (e.g. nursing, physician's associate) may be substituted if ...

Investigate and analyze potential and actual professional liability and general liability exposures ... A Bachelor's degree in a clinical field (e.g. nursing, physician's associate) may be substituted if ...

Investigate and analyze potential and actual professional liability and general liability exposures ... A Bachelor's degree in a clinical field (e.g. nursing, physician's associate) may be substituted if ...

Investigate and analyze potential and actual professional liability and general liability exposures ... A Bachelor's degree in a clinical field (e.g. nursing, physician's associate) may be substituted if ...

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Associate Quantitative Risk Analyst information

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How much do associate quantitative risk analyst jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for associate quantitative risk analyst in Raleigh, NC is $39.36, according to ZipRecruiter salary data. Most workers in this role earn between $28.99 and $47.88 per hour, depending on experience, location, and employer.

What is an associate quantitative risk analyst?

Associate Quantitative Risk Analysts are entry- to mid-level professionals who help financial institutions and organizations assess and manage risk using mathematical models and statistical techniques. They analyze data to identify potential risks, develop risk management strategies, and support decision-making processes. Their work often involves using quantitative software, working with large datasets, and collaborating with other risk management and finance professionals. Typically, they have backgrounds in mathematics, statistics, finance, or related fields.

What are the key skills and qualifications needed to thrive as an associate quantitative risk analyst?

To thrive as an Associate Quantitative Risk Analyst, you need a strong background in mathematics, statistics, finance, and data analysis, typically supported by a relevant degree such as in finance, mathematics, or economics. Familiarity with statistical software (like R, SAS, or Python), financial modeling tools, and possibly certifications such as FRM or CFA is highly valuable. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting complex data and presenting findings. These competencies are essential for accurately assessing financial risks and supporting informed decision-making in risk management environments.

What are some common challenges faced by associate quantitative risk analysts in their first year, and how can they overcome them?

In their first year, Associate Quantitative Risk Analysts often encounter challenges such as adapting to complex financial models, learning to interpret large datasets, and effectively communicating technical findings to non-technical stakeholders. Navigating regulatory requirements and understanding the company's risk management framework can also be demanding. To overcome these obstacles, new analysts should proactively seek mentorship, participate in team discussions, and leverage internal training resources to build both technical and soft skills. Regular collaboration with colleagues in risk, finance, and IT departments can also provide valuable insights and accelerate professional growth.

What is the difference between Associate Quantitative Risk Analyst vs Credit Risk Analyst?

AspectAssociate Quantitative Risk AnalystCredit Risk Analyst
Required CredentialsBachelor's in finance, economics, or related field; often some familiarity with quantitative methodsBachelor's in finance, economics, or related field; certifications like CFA or FRM are common
Work EnvironmentFinancial institutions, risk management teams, quantitative departmentsBanking, lending institutions, credit departments
Employer & Industry UsageUsed in risk modeling, data analysis, and quantitative assessmentsFocuses on assessing creditworthiness and loan risk

The Associate Quantitative Risk Analyst primarily focuses on developing models and analyzing data to measure financial risks, often working with quantitative tools. In contrast, a Credit Risk Analyst concentrates on evaluating the creditworthiness of borrowers and managing credit risk. While both roles require similar educational backgrounds and work within financial institutions, their core responsibilities differ—one emphasizes quantitative modeling, the other credit assessment.

What are the most commonly searched types of Quantitative Risk Analyst jobs in Raleigh, NC?

The most popular types of Quantitative Risk Analyst jobs in Raleigh, NC are:

What are popular job titles related to Associate Quantitative Risk Analyst jobs in Raleigh, NC?

For Associate Quantitative Risk Analyst jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Associate Quantitative Risk Analyst jobs in Raleigh, NC look for?

The top searched job categories for Associate Quantitative Risk Analyst jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Associate Quantitative Risk Analyst jobs?

Cities near Raleigh, NC with the most Associate Quantitative Risk Analyst job openings:

Model Risk Analyst

NC SECU

Raleigh, NC • Hybrid

Full-time

Re-posted 9 days ago


Job description

If you are motivated and believe in the credit union philosophy of "People Helping People," join our team!

Position Overview:

Assist in the development, implementation, and maintenance of the Model Risk Management (MRM) program within SECU through the development and validation of statistical models, qualitative models, and models developed with other quantitative algorithms.

Essential Responsibilities:

  • (40%) Execute model validation activities across the model life-cycle including model validations, ongoing performance evaluation, and tracking model findings to ensure models across SECU are conceptually sound relative to their intended use and performing appropriately. Execute end-to-end testing plans for validation and review of SECU's statistical and qualitative models with oversight and guidance from supervisor and other senior validation staff.
  • (30%) Validate the performance and controls of statistical models using provided model development documentation and communications with model developers. Document and present findings to management and model owners.
  • (10%) Provide input for enhancements to the model risk management framework, including maintaining model inventory and model risk rankings.
  • (10%) Develop and maintain effective partnerships within SECU, particularly with model owners, model developers and data analysts.
  • (10%) Assist in implementation of, and adherence to, the MRM Policy and associated model risk SOPs across SECU.

Required Education & Experience (Knowledge, Skills, & Abilities):

  • Bachelors in a quantitative discipline (Economics, statistics, finance, data science or analytics, math, physics, or related field)
  • 3+ years of experience in modeling or analytics
  • Ability to assess model conceptual design, backtesting of model results, assumptions, controls over data flows, model execution, and compliance of model results with intended application by model users.
  • Advanced programming skills in a statistical programming language, such as SAS, R, or Python. Ability to write computer code to perform analysis on complex modeling and analytical challenges and to review code written by others for accuracy and efficiency, with minimal guidance from supervisor.
  • Academic and/or professional understanding of advanced mathematical and statistical modeling techniques, including logistic regression, time series analysis, linear regression, Monte Carlo simulation, Artificial Intelligence/Machine Learning (AI/ML) techniques, etc.
  • Demonstrated ability to contribute to multiple projects simultaneously under guidance from supervisor.
  • Strong oral and written communication skills. Experience contributing to detailed technical validation reports and/or model development documentation.
  • Strong attention to detail and the ability to understand and analyze complex modeling and analytical challenges with some guidance from supervisor and senior staff.
  • Perform job functions independently with some day-to-day oversight from supervisor.

Preferred Education & Experience (Knowledge, Skills, & Abilities):

  • Masters in quantitative discipline
  • Experience in financial services or consulting industry
  • Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR, ALM, loan pricing and/or mortgage servicing rights, derivatives, Compliance (BSA/AML/OFAC), Liquidity, or Fraud
  • Subject matter expertise in generative large language models (Artificial Intelligence)

Job Environment & Physical Requirements:

  • Hybrid expectations
  • Sitting for prolonged periods
  • Computer for prolonged periods

SECU provides equal employment opportunity to all qualified persons regardless of race, color, religion, age, sex, sexual orientation, gender identity, national origin, genetic information, disability, veteran status, or other classification protected by law.

Disclaimer

State Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.