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Quantitative Risk Modeler Jobs in Dallas, TX (NOW HIRING)

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Quantitative Risk Modeler information

See Dallas, TX salary details

$96.9K

$167.9K

$256.7K

How much do quantitative risk modeler jobs pay per year?

As of Jul 6, 2026, the average yearly pay for quantitative risk modeler in Dallas, TX is $167,901.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,100.00 and $196,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Quantitative Risk Modeler position, and why are they important?

To thrive as a Quantitative Risk Modeler, you need strong quantitative analysis skills, advanced knowledge of statistics, mathematics, and finance, and typically a degree in a quantitative field such as mathematics, finance, or engineering. Proficiency with programming languages like Python, R, or MATLAB, and familiarity with risk management systems and financial modeling software are commonly required, as are certifications such as FRM or CFA. Excellent problem-solving abilities, attention to detail, and effective communication skills are critical for interpreting data and conveying complex concepts to non-technical stakeholders. These skills ensure accurate risk assessment, effective model development, and successful collaboration within cross-functional teams in high-stakes financial environments.

What are the primary responsibilities of a Quantitative Risk Modeler on a daily basis?

A Quantitative Risk Modeler’s typical day involves developing, testing, and validating quantitative models used to assess financial risks such as credit, market, or operational risk. You’ll often work with large datasets, use statistical and computational methods to analyze risk exposures, and document your findings for regulatory compliance. Collaboration with traders, risk managers, and other data professionals is common to ensure models accurately reflect real-world financial conditions. Additionally, you may be involved in meetings to discuss model outcomes, propose improvements, and stay updated on the latest regulatory and industry standards.

What is a Quantitative Risk Modeler job?

A Quantitative Risk Modeler assesses financial risks by developing mathematical models and statistical techniques to analyze market, credit, and operational risks. They use programming, data analysis, and financial theories to quantify risk exposure and support decision-making in banks, investment firms, and risk management teams. Their work involves stress testing, scenario analysis, and creating predictive models to enhance risk assessment and regulatory compliance.

What are popular job titles related to Quantitative Risk Modeler jobs in Dallas, TX? For Quantitative Risk Modeler jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Modeler jobs in Dallas, TX look for? The top searched job categories for Quantitative Risk Modeler jobs in Dallas, TX are:
Infographic showing various Quantitative Risk Modeler job openings in Dallas, TX as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $167,901 per year, or $80.7 per hour.
Head of CCB Auto and Business Banking Portfolio Risk Modeling

Head of CCB Auto and Business Banking Portfolio Risk Modeling

JP Morgan Chase

Plano, TX

Full-time

Medical, Retirement

Posted 10 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 486 frontline employees who took The Breakroom Quiz

54th of 144 rated banks


Job description

Lead a global team of quantitative experts to design, deliver, and govern bestinclass predictive models that power valuation, credit reserving, stress testing, budgeting, and risk assessment for CCB's Auto and Business Banking lending portfolios. You will own the endtoend modeling lifecycle and translate model insights into actions that shape portfolio strategy and risk outcomes. The CCB Portfolio Risk Modeling Center of Excellence brings together economists, statisticians, mathematicians, and analytics professionals to quantify and manage lending risks across Consumer & Community Banking. The team applies advanced methods to one of the world's largest consumer lending datasets, partnering across JPMC to assess, measure, and manage critical risks across CCB portfolios.

Job Responsibilities

  • Lead and develop a highperforming global team building predictive risk models for CCB's Auto and Business Banking lending portfolios.
  • Own the endtoend modeling lifecycle (data sourcing, design, estimation, validation readiness, implementation, deployment, performance monitoring, and periodic recalibration).
  • Ensure compliance with Firmwide model risk management standards and applicable regulatory expectations (e.g., SR 117/OCC 201112), with strong documentation, controls, and audit readiness.
  • Deliver clear, decisionuseful insights based on models and scenario analyses that inform credit strategy, reserving (e.g., CECL), stress testing, portfolio valuation, and budgeting.
  • Advance the modeling roadmap by modernizing data pipelines, feature engineering, and model operations practices; drive process efficiency and reproducibility.
  • Partner with Product, Risk, Finance, Technology, and Model Risk teams to align models with business objectives and ensure robust change management and governance.
  • Establish model monitoring frameworks, performance thresholds, and action plans; proactively identify model, data, or process risks and drive remediation.
  • Recruit, mentor, and retain talent; promote a culture of scientific rigor, delivery excellence, and inclusive leadership.

Required qualifications, Capabilities, and Skills

  • Ph.D. (or comparable advanced degree) in Economics, Statistics, Operations Research, Mathematics, or a related quantitative field; or equivalent experience.
  • 10+ years building and deploying predictive risk models for consumer lending portfolios, with deep domain knowledge in auto and business banking credit.
  • 5+ years leading and developing highperforming quantitative teams.
  • Expertise across advanced modeling methods (e.g., parametric and nonparametric regression, time series, survival/PDLGDEAD frameworks, machine learning).
  • Proficiency in Python and/or R; familiarity with SAS; strong SQL and experience with largescale datasets.
  • Demonstrated ability to communicate complex analytics succinctly and influence senior stakeholders.
  • Strong analytical judgment and problem solving; track record of improving processes and controls.

Preferred qualifications, Capabilities, and Skills

  • Experience with CECL/allowance modeling, capital stress testing, and scenario design.
  • Familiarity with model risk governance, validation expectations, and audit processes.
  • Experience with modern data and model operations tooling (e.g., Spark, Git, CI/CD, workflow orchestration) and collaboration with Technology/Engineering teams.
  • Exposure to cloudbased analytics environments and secure model deployment at scale.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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