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Quantitative Risk Analyst Jobs in Minnesota (NOW HIRING)

Allianz

AIM Analyst - Hedging | Hybrid

Minneapolis, MN · On-site

Contribute to quantitative analysis projects. You will report to the AIM AVP - Portfolio Management ... For additional information regarding What It's Like To Work Here | Allianz Life . 95743 | Risk ...

HealthPartners

Data Analyst Principal

Bloomington, MN · On-site

$48.37 - $74.97/hr

... development, risk assessment and indexing, as well as domain-specific measurements (example ... quantitative field. Alternate experience and education in equivalent areas is acceptable.

Varsity Tutors

Business Statistics Tutor

Saint Paul, MN · Remote

$40/hr

... quantitative coursework. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... risk analysis. * Curriculum Awareness & Adaptive Instruction: Familiar with business statistics ...

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Quantitative Risk Analyst information

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$55.3K

$131.1K

$235.1K

How much do quantitative risk analyst jobs pay per year?

As of May 29, 2026, the average yearly pay for quantitative risk analyst in Minnesota is $131,121.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,200.00 and $142,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Quantitative Risk Analyst, and why are they important?

To thrive as a Quantitative Risk Analyst, you need strong analytical and mathematical skills, experience with statistical modeling, and typically a degree in finance, mathematics, statistics, or a related field. Proficiency in programming languages such as Python, R, or MATLAB, and familiarity with risk management systems and financial databases are important technical requirements. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for explaining complex analyses to stakeholders. These skills are crucial for accurately identifying, measuring, and mitigating financial risks in dynamic market environments.

What are some common challenges a Quantitative Risk Analyst faces when integrating new data sources into risk models?

Quantitative Risk Analysts often encounter challenges related to data quality, consistency, and compatibility when integrating new data sources into risk models. Ensuring that the data is accurate, timely, and relevant requires rigorous validation and sometimes complex data cleaning processes. Additionally, analysts must adapt existing risk models to accommodate new variables, which may involve re-calibrating parameters or even restructuring parts of the model. Effective collaboration with IT and data engineering teams is essential to streamline data integration and maintain model reliability.

What is a Quantitative Risk Analyst?

A Quantitative Risk Analyst is a professional who uses mathematical models, statistical techniques, and data analysis to assess and manage financial risks within an organization. They typically evaluate potential losses from market movements, credit defaults, or operational failures and help develop strategies to mitigate those risks. Their work is crucial in industries such as banking, investment, insurance, and asset management, where understanding and controlling risk is essential for financial stability and compliance. Quantitative Risk Analysts often work with complex financial instruments and large datasets, requiring strong analytical and programming skills.

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

AspectQuantitative Risk AnalystCredit Risk Analyst
Required CredentialsDegree in finance, economics, or mathematics; certifications like FRM or CFADegree in finance, economics, or related; certifications like FRM or CFA often preferred
Work EnvironmentFinancial institutions, investment firms, risk management departmentsBanks, lending institutions, credit agencies
Employer & Industry UsageUsed across finance sectors for risk modeling and analysisPrimarily in banking and lending for assessing creditworthiness
Comparison Search IntentUnderstanding differences in risk analysis rolesDistinguishing credit-specific risk roles from broader risk analysis

While both roles involve risk assessment and require similar credentials, a Quantitative Risk Analyst focuses on modeling and analyzing various financial risks using quantitative methods across multiple risk types. In contrast, a Credit Risk Analyst specializes in evaluating creditworthiness and managing credit risk specifically within lending and banking sectors.

What are popular job titles related to Quantitative Risk Analyst jobs in Minnesota? For Quantitative Risk Analyst jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Quantitative Risk Analyst jobs in Minnesota look for? The top searched job categories for Quantitative Risk Analyst jobs in Minnesota are:
Quantitative Risk Analyst jobs near you
Integration and Automation Leader - Credit Risk Modeling

Integration and Automation Leader - Credit Risk Modeling

US Bank

Minneapolis, MN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

U.S. Bank rating

8.2

Company rating: 8.2 out of 10

Based on 344 frontline employees who took The Breakroom Quiz

37th of 141 rated banks

Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

We are looking for a strategic and results-driven quantitative leader to lead partnering with technology and lead automation initiatives within the Credit Risk Model Operations and Strategy team, as part of the Model Development and Decision Science (MDDS) organization. This role will focus on redesigning and optimizing key processes across the model lifecycle-including implementation, production, and performance monitoring-as we migrate from SAS to Azure Databricks and Python.

About the CRA Team

We are a highly dynamic and talented team which delivers on our mission through four pillars: Customer, Process, Talent, and Data.

Vision | We create the future of credit risk management through data, analytics, and risk process innovation for our customers.

Mission | We deliver data-driven information solutions to protect our stakeholders and inform the most significant financial decisions in the bank.

Values | In addition to U.S. Bank core values, we prioritize collaboration, integrity, simplicity, and continuous learning.

About the Role

We are seeking a strategic and technically skilled leader to partner with technology and drive automation within the Credit Risk Model Development and Decision Science (MDDS) team. This role will focus on enhancing model production, model monitoring, model implementation, reporting, and documentation capabilities through the development and maintenance of reusable code libraries, robust data source connections, containerized environments, testing and execution pipelines. The leader will also lead evaluation, selection, onboarding, and lifecycle maintenance of any third-party tools and platforms leveraged by the Credit Risk Model Development and Decision Science (MDDS) team. You will be responsible for designing systems and processes for model development, production, monitoring, and implementation. The models support loan portfolio stress testing (CCAR), the allowance for credit losses (ACL / CECL), counterparty risk, and commercial risk rating scorecards. The ideal candidate will have hands-on experience in system design, a strong foundation in data science, and proficiency in quantitative programming languages.

Key Activities

This role centers on helping our team migrate our model infrastructure from SAS to Azure Databricks and Python. The emphasis is on building strong architectural foundations that support repeatable processes, improve efficiency, and facilitate automation. This role will partner with technology to lead the selection, onboarding, and maintenance of technology tools and platforms used in model operations and redesigning processes to be modular, scalable, and well-controlled.

The processes in scope for this role include:

  • Model development - build repeatable, standardized processes and tools for model development.

  • Implementation - scalable tools to onboard models into production.

  • Production - platforms for executing models for core production purposes.

  • Monitoring - automated systems to track and assess model performance.

  • Reporting - integrations and pipelines for dashboards and formatted output delivery.

Core Competencies:

  • Strong understanding of technology including fundamental software engineering principles, automation tools, cloud-based tools and infrastructure, database systems, and dashboard/visualization tools particularly in support of modeling /quantitative platforms.

  • Exceptional leadership skills and ability to drive initiatives that span multiple teams and stakeholders.

  • A mindset for collaboration, customer centricity, and risk management.

  • Experience with risk modeling and data at large regulated financial institutions.

  • Familiarity with AI-driven tools and automation platforms (e.g., Microsoft Copilot, Microsoft Power Platform) to streamline data operations and accelerate data delivery.

Innovation & Automation Leadership

  • Design, build, and maintain reusable code libraries and frameworks to support model development, implementation, production and monitoring activities.

  • Partner with technology to lead the selection, onboarding, and maintenance of technology tools and platforms used in model operations.

  • Develop and manage automated data pipelines and containerized environments (e.g., Docker, Kubernetes) for scalable data processing, model operations.

  • Implement orchestration tools (e.g., Apache Airflow) to streamline model operations workflows, reporting, and documentation.

Training & Enablement

  • Develop and deliver onboarding programs for new team members, focusing on tooling, infrastructure, and best practices.

  • Provide ongoing training and support to ensure effective use of automation tools and libraries.

  • Foster a culture of continuous learning and innovation within the team.

Stakeholder Engagement

  • Partner with model developers and model operations to assess and meet their technological needs in a timely and effective manner.

  • Contribute to reporting and presentations for senior management and risk committees.

Basic Qualifications

  • Bachelor's degree in a quantitative field, and 10 or more years of relevant experience
    OR

  • MA/MS in a quantitative field, and six or more years of related experience
    OR

  • PhD in a quantitative field, and five or more years of related experience


Preferred Skills/Experience

  • Object-oriented python programming

  • Databricks experience required in model development, model production, and/or model monitoring.

  • Relational databases, SQL query optimization

  • Code management and version control using Git

  • AI/ML and generative AI approaches

  • Strong project management and organizational skills

LOCATION EXPECTATIONS: This role requires working from a U.S. Bank Location three (3) or more days per week.

If there's anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to ourdisability accommodations for applicants.

Benefits:

Our approach to benefits and total rewards considers our team members' whole selves and what may be needed to thrive in and outside work. That's why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following:

  • Healthcare (medical, dental, vision)

  • Basic term and optional term life insurance

  • Short-term and long-term disability

  • Pregnancy disability and parental leave

  • 401(k) and employer-funded retirement plan

  • Paid vacation (from two to five weeks depending on salary grade and tenure)

  • Up to 11 paid holiday opportunities

  • Adoption assistance

  • Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Review our full benefits available by employment status here.

U.S. Bank is an equal opportunity employer. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and other factors protected under applicable law.

E-Verify

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories. The E-Verify program is an Internet-based employment eligibility verification system operated by the U.S. Citizenship and Immigration Services. Learn more about theE-Verify program.

The salary range reflects figures based on the primary location, which is listed first. The actual range for the role may differ based on the location of the role. In addition to salary, U.S. Bank offers a comprehensive benefits package, including incentive and recognition programs, equity stock purchase 401(k) contribution and pension (all benefits are subject to eligibility requirements). Pay Range: $133,365.00 - $156,900.00

U.S. Bank will consider qualified applicants with arrest or conviction records for employment. U.S. Bank conducts background checks consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act as well as the San Francisco Fair Chance Ordinance. U.S. Bank is subject to, and conducts background checks consistent with the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA). In addition, certain positions may also be subject to the requirements of FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or federal guidelines applicable to an agreement, such as those related to ethics, safety, or operational procedures.

Applicants must be able to comply with U.S. Bank policies and procedures including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.

Posting may be closed earlier due to high volume of applicants.

What U.S. Bank employees say

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About U.S. Bank

Sourced by ZipRecruiter

U.S. Bank is a reputable and established financial institution that plays a significant role in the banking sector. With a history spanning over 150 years, U.S. Bank has built a strong foundation of trust and reliability. As a comprehensive bank, they offer a wide array of financial products and services to cater to the diverse needs of their customers, including individuals, businesses, and communities. Customer satisfaction is of utmost importance to U.S. Bank. They prioritize delivering exceptional service and fostering long-term relationships with their clients. Through their extensive network of branches and advanced digital banking platforms, U.S. Bank ensures convenient access to their services, empowering customers to manage their finances efficiently and securely.

Industry

Banking and credit intermediation

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

Year founded

1863

Social media

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