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Internship Quantitative Risk Modeler Jobs in Texas

DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays ... FR&G collaborates closely with Quantitative Risk Management and the Counterparty Credit Risk teams ...

Collaborate with quantitative analysts to refine model assumptions, validate model outputs, and ensure accuracy in risk measurement. * Apply advanced statistical techniques and machine learning ...

... Quantitative Cost Risk Analysis: * Lead full Monte Carlobased cost and schedule risk analyses using Primavera Risk Analysis (PRA), @Risk, Safran, or equivalent tools. * Build and validate risk models ...

Quantitative Strategist (PhD)

Austin, TX · On-site

$175K - $200K/yr

Develop risk models and frameworks to manage portfolio risks * Create tools to automate research ... No previous Quant Finance or specific asset class experience required. * History of diverse ...

DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays ... FR&G collaborates closely with Quantitative Risk Management and the Counterparty Credit Risk teams ...

Develop and maintain risk models, reports, and dashboards to support decision-making * Monitor ... Strong analytical and quantitative skills * Proficiency in Microsoft Excel and data analysis tools

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Internship Quantitative Risk Modeler information

What is the difference between Internship Quantitative Risk Modeler vs Quantitative Risk Analyst?

AspectInternship Quantitative Risk ModelerQuantitative Risk Analyst
CredentialsTypically pursuing or recent graduate in finance, mathematics, or related fieldsOften requires a degree in finance, economics, or quantitative disciplines; certifications like FRM or CFA are common
Work EnvironmentInternship setting, learning-focused, supervised by senior staffFull-time professional role, responsible for risk assessment and modeling
Employer & Industry UsageUsed in banks, asset management firms, and financial institutions for training and entry-level rolesCommon in financial services, banking, and investment firms for ongoing risk management

The Internship Quantitative Risk Modeler is an entry-level, learning-focused role typically held by students or recent graduates, whereas the Quantitative Risk Analyst is a full-time professional responsible for analyzing and managing risk using quantitative models. The internship provides foundational experience, while the analyst role involves ongoing risk assessment and decision-making.

What job categories do people searching Internship Quantitative Risk Modeler jobs in Texas look for? The top searched job categories for Internship Quantitative Risk Modeler jobs in Texas are:
What cities in Texas are hiring for Internship Quantitative Risk Modeler jobs? Cities in Texas with the most Internship Quantitative Risk Modeler job openings:

Senior Credit Risk Modeling Analyst

TriQuest Business Services

San Antonio, TX • Hybrid

$115K/yr

Other

Posted 6 days ago


Job description

Job Title: Senior Credit Risk Modeling Analyst

Location: San Antonio, TX (Hybrid)
Salary: $115,000
Industry: Financial Services / Credit Risk


About the Role

We are seeking a highly analytical Senior Credit Risk Modeling Analyst to help build and lead the next generation of credit underwriting models within a growing financial institution. This is a ground-floor opportunity to bring credit risk modeling in-house, moving the organization from reporting-focused analytics to advanced, data-driven decisioning.

You will serve as the subject matter expert on a small team, owning the full model lifecycle-from development and validation to monitoring and optimization-while helping elevate the team's overall modeling capabilities.


Key Responsibilities

Model Development & Strategy

  • Design and develop credit risk models for loan underwriting using internal and external data
  • Lead major model refresh initiatives using historical application and performance data
  • Build decision-tree and predictive models to improve approval strategies and risk outcomes

Model Lifecycle Ownership

  • Own end-to-end model lifecycle: development, documentation, validation, and deployment
  • Monitor model performance and identify trends or deviations from expectations
  • Recommend and implement enhancements based on performance insights

Data & Tools

  • Work within Databricks using SQL and Python for data extraction, transformation, and modeling
  • Integrate internal datasets with third-party data sources (e.g., Experian)
  • Support model deployment within external platforms (e.g., PCOE / Strategy Design Studio)

Collaboration & Stakeholder Engagement

  • Partner with analysts to support reporting, testing, and monitoring efforts
  • Work with audit, risk, and leadership teams to defend model assumptions and decisions
  • Collaborate with external vendors on model implementation and optimization
  • Communicate complex modeling concepts to both technical and non-technical stakeholders

Qualifications
  • Bachelor's degree in Finance, Statistics, or a quantitative field (Master's preferred)
  • 5+ years of experience in credit risk modeling or similar quantitative role
  • Hands-on experience building and validating credit risk or underwriting models
  • Strong experience with SQL and Python (R or other tools a plus)
  • Experience working in a regulated financial environment (bank or credit union preferred)
  • Ability to explain and defend models under audit and regulatory review
  • Strong analytical thinking and problem-solving skills

Preferred Experience
  • Experience with Experian PCOE / Strategy Design Studio
  • Exposure to CECL or credit loss modeling frameworks
  • Experience integrating third-party credit bureau data into models
  • Background working with Databricks or similar data platforms

Work Environment & Culture
  • Hybrid schedule (~30% onsite; team works in-office on designated weeks)
  • Collaborative, high-growth environment with a small, developing team
  • Leadership style is hands-off, with strong support for removing roadblocks
  • Opportunity to shape and expand the organization's credit risk modeling function