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Associate Quantitative Risk Analyst Jobs in Utah

Contribute to the enhancement of data quality procedures and risk controls. * Cross-Functional ... Strong analytical and quantitative skills. * Previous experience with vended software, like Moody ...

SOX Manager

Draper, UT

$94K - $125K/yr

Risk Assessment & Scoping: Perform the annual qualitative and quantitative risk assessment to ... Analytical Thinking: Strong conceptual and problem-solving skills with meticulous attention to ...

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Associate Quantitative Risk Analyst information

What does a quantitative risk analyst do?

A quantitative risk analyst evaluates financial risks using mathematical models and statistical techniques to identify potential losses and inform decision-making. They analyze data, develop risk assessment tools, and often use software like Excel, R, or Python to support risk management strategies. Strong analytical skills and knowledge of finance and statistics are essential for this role.

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.

Is a quant analyst a high paying job?

A quantitative risk analyst typically earns a competitive salary, especially in finance and investment firms, with compensation often increasing with experience, advanced degrees, and specialized skills in programming and statistical analysis. While salaries vary by location and employer, the role is generally considered well-paying within the finance industry.

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.

How much does a quant risk analyst make?

The average salary for a quantitative risk analyst at Morgan Stanley is typically between $80,000 and $150,000 annually, depending on experience, location, and level of seniority. Entry-level positions may start lower, while experienced analysts with advanced skills in programming and risk modeling can earn higher compensation, often supplemented with bonuses and benefits.

What is the salary of a quant risk analyst?

The salary of a quantitative risk analyst typically ranges from $70,000 to $150,000 annually, depending on experience, location, and the complexity of the role. Entry-level positions may start lower, while experienced analysts with advanced skills in programming and risk modeling can earn higher compensation, often supplemented with bonuses and benefits.

What are Associate Quantitative Risk Analysts?

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, and why are they important?

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.
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CECL Analyst

CECL Analyst

First Electronic Bank

Salt Lake City, UT • On-site

Other

Posted 11 days ago


Job description

Description

At First Electronic Bank (FEB), we are driven by the purpose to make credit accessible to everyday Americans, and their businesses. Partnering with some of the most innovative FinTech companies in the nation, we offer a wide range of consumer and commercial credit products on a national basis. Offering revolving lines of credit, private-label credit cards, installment financing programs and more, FEB's engages with strategic, collaborative partnerships, promoting services and products to provide the most beneficial consumer and commercial financing solutions.     


The CECL Analyst supports the organization's Current Expected Credit Losses (CECL) modeling, reporting, and analysis. This role assists in collecting, validating, and analyzing loan portfolio data to support allowance calculations, risk assessments, regulatory reporting, and management presentations. The ideal candidate has strong analytical skills, attention to detail, and a desire to grow within credit risk and financial modeling.


What You'll Do:

  • CECL Data & Modeling Support
  • Assist with preparing and validating monthly/quarterly CECL dataset inputs, ensuring accuracy and completeness.
  • Support the execution of CECL models, including probability of default (PD), loss given default (LGD), and prepayment models.
  • WARM methodology and Static Pool/Vintage Loss analysis.
  • Help maintain model documentation and version control.
  • Analysis & Reporting
  • Assist in generating CECL allowance calculations and variance analyses.
  • Prepare supporting schedules, workpapers, and dashboards for internal stakeholders and auditors.
  • Identify trends in portfolio performance, credit quality, and model outputs.
  • Controls, Compliance & Audit Support
  • Support internal and external audit requests related to CECL processes and controls.
  • Ensure CECL processes align with regulatory guidance and internal policies.
  • Contribute to the enhancement of data quality procedures and risk controls.
  • Cross-Functional Collaboration
  • Partner with Credit, Finance, Accounting, and Data teams to gather required inputs and clarify assumptions.
  • Support ad hoc analysis and special projects related to credit risk, loan portfolio performance, or regulatory changes.


Requirements

What We're Looking For:

  • Degree in Finance, Economics, Accounting, Mathematics, Statistics, Data Analytics, or related field.
  • Strong analytical and quantitative skills.
  • Previous experience with vended software, like Moody's Portfolio Analyzer or Impairment Studio preferred.
  • Proficiency in Excel; basic familiarity with SQL, R, Python, and data visualization tools.
  • Ability to work with large datasets and identify discrepancies.
  • Strong organizational skills and attention to detail.

Preferred Qualifications

  • 5+ years of experience in financial services, banking, credit risk, accounting, or data analytics.
  • Exposure to CECL methodology, ALLL, or other credit modeling frameworks.
  • Experience with loan servicing or core banking systems.
  • Understanding of credit risk metrics and loan portfolio structures.


Key Competencies

  • Analytical thinking
  • Problem-solving
  • Data accuracy and precision
  • Ability to manage multiple priorities
  • Strong communication skills
  • Initiative and willingness to learn complex financial concepts