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Phd Quant Jobs in Minnesota (NOW HIRING)

Quantitative Modeler Manager - AML

Minneapolis, MN · On-site

$57.25 - $74/hr

Basic Qualificati ons - 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 ...

... quantitative and/or qualitative analytical skills. Minimum of 6 years of experience or recent PhD. Demonstrated proficiency in implementing project analysis plans, including the ability to direct and ...

Senior Health Services Analyst

Rochester, MN · Hybrid

$89K - $118K/yr

... quantitative and/or qualitative analytical skills. Minimum of 6 years of experience or recent PhD. Demonstrated proficiency in implementing project analysis plans, including the ability to direct and ...

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Phd Quant information

See Minnesota salary details

$96K

$166.2K

$254.2K

How much do phd quant jobs pay per year?

As of Aug 5, 2026, the average yearly pay for phd quant in Minnesota is $166,234.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,700.00 and $194,900.00 per year, depending on experience, location, and employer.

What is a PhD Quant?

A PhD Quant, short for Quantitative Analyst with a PhD, is a professional who uses advanced mathematical, statistical, and computational techniques to analyze financial markets and develop complex models for trading, risk management, or investment strategies. They typically work in banks, hedge funds, or financial technology firms. PhD Quants leverage their deep expertise in fields like mathematics, physics, computer science, or engineering to solve challenging problems and gain insights that drive financial decision-making. Their work often involves programming, data analysis, and the implementation of quantitative models.

What are the typical collaboration dynamics for a PhD Quant within a financial institution?

PhD Quants frequently work in close collaboration with traders, risk managers, and software engineers to develop and implement quantitative models for pricing, risk assessment, and trading strategies. While a significant portion of the work involves independent research and model development, regular meetings and cross-functional teamwork are essential to ensure models align with business objectives and regulatory requirements. Effective communication skills are important, as PhD Quants often need to explain complex mathematical concepts to colleagues with varying technical backgrounds.

What are the key skills and qualifications needed to thrive as a PhD Quant?

To thrive as a PhD Quant, you need a strong background in mathematics, statistics, and programming, typically supported by a PhD in a quantitative field such as mathematics, physics, finance, or engineering. Expertise in technical tools such as Python, C++, R, and experience with statistical modeling systems and quantitative finance libraries is expected. Analytical thinking, problem-solving abilities, and effective communication are standout soft skills in this role. These skills and qualities are crucial for developing complex models, interpreting data accurately, and collaborating across multidisciplinary teams in high-stakes financial environments.

Do quant firms hire PhDs?

Quant firms frequently hire PhDs, especially in fields like mathematics, physics, engineering, and computer science, to develop and implement quantitative trading strategies. These roles often require strong analytical skills, programming proficiency in languages such as Python or C++, and a deep understanding of financial models. PhDs are valued for their research experience and ability to handle complex data analysis in a fast-paced environment.

How much do PhD quants make?

PhD quants typically earn between $150,000 and $300,000 annually, with compensation increasing based on experience, location, and the complexity of models used. Many also receive bonuses and profit-sharing, especially in hedge funds and investment banks. Advanced quantitative skills in programming and statistical analysis are highly valued in this field.

What is the difference between Phd Quant vs Quant Analyst?

AspectPhd QuantQuant Analyst
Required CredentialsPhD in Mathematics, Statistics, or related fieldBachelor's or Master's degree, often with quantitative skills
Work EnvironmentResearch-focused, often in finance or hedge fundsTrading floors, financial institutions, or asset management firms
Industry UsagePrimarily in hedge funds, investment banks, and proprietary tradingIn asset management, hedge funds, and banks

The main difference between a Phd Quant and a Quant Analyst lies in their educational background and focus. Phd Quants typically hold doctoral degrees and focus on developing complex models and research, while Quant Analysts often have master's or bachelor's degrees and focus on applying models to trading strategies. Both roles are integral to quantitative finance but differ in scope and depth of research.

What job categories do people searching Phd Quant jobs in Minnesota look for? The top searched job categories for Phd Quant jobs in Minnesota are:
What cities in Minnesota are hiring for Phd Quant jobs? Cities in Minnesota with the most Phd Quant job openings:
Infographic showing various Phd Quant job openings in Minnesota as of June 2026, with employment types broken down into 71% Full Time, and 29% Part Time. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution, with an average salary of $166,234 per year, or $79.9 per hour.

Senior Quant, Artificial Intelligence/Machine Learning

U.S. Bank

Minneapolis, MN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


U.S. Bank rating

8.2

Company rating: 8.2 out of 10

Based on 360 frontline employees who took The Breakroom Quiz

52nd of 170 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're looking for a sharp individual contributor who's adept at advanced AI/ML algorithms and their applications in financial institutions to join our AI/ML Validation Center of Excellence in Model Risk Management. The team plays a critical role in providing oversight to U.S. Bank's Artificial Intelligence Models across various business areas, such as Marketing, Fraud, Credit Risk and Bank Operations.
As a Senior Quant you will develop benchmark AI/ML models, provide validation expertise and consulting services related to AI/ML model development and model review, including best practices on algorithm development and selection, performance evaluation, implementation, monitoring, model risk mitigation and remediation. In addition, you will be responsible for conducting R&D for various AI/ML methodologies and their potential applications and use cases.
Deliverables include reviewing model development documentation, independently testing of advanced AI/ML and Generative AI & Agentic AI models, developing technical guidance documents, training curriculum and white paper, and communicating model requirements and validation outcome to stakeholders within the Bank.
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
- Strong statistical modeling or computer science background and hands on model development or validation skills
- Strong programming skills using Python packages such as Numpy, Pandas, and scikit-learn.
- Considerable knowledge of various machine learning algorithms and their applications, including Random Forest, GBM, XGBoost, deep learning, NLP, computer vision, and LLM.
- Hands-on experience designing, developing, and deploying advanced deep learning architectures, including MLPs, RNNs, CNNs, and other state-of-the-art neural network frameworks for a wide range of AI and machine learning applications.
- Deep expertise in advanced Agentic AI architectures and orchestration patterns, including function calling, MCP, SKILLs, A2A, context engineering, harness engineering, loop engineering, and other emerging frameworks for building scalable, multi-agent AI systems.
- Strong expertise in building, deploying, and evaluating GenAI and Agentic AI solutions, including RAG, multi-agent systems, tool-augmented workflows, and advanced evaluation techniques such as adversarial testing, semantic similarity analysis, retrieval assessment, and LLM-as-a-Judge methodologies.
- Hands-on experience with modern AI development, deployment, and evaluation ecosystems, including PyTorch, TensorFlow/Keras, Hugging Face Transformers, LangChain, LangGraph, OpenAI Agent SDK, AI-assisted development platforms such as Claude Code and GitHub Copilot, and LLM evaluation frameworks including DeepEval, LlamaIndex, Ragas, and other comparable tools.
- Familiarity with cloud-based AI platforms and services, including AWS Bedrock, Azure AI, Microsoft Copilot, Google Vertex AI, vector databases, and model serving/inference platforms.
- Research experience and publications on AI or Gen AI are preferred
- Experience in financial industry is preferred but not required
- Advanced understanding of Model Risk Management and OCC SR 26-2 is a plus
- Demonstrated independence, teamwork and leadership skills
- Strong project management skills
- Excellent written and verbal communication 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 our disability 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 the E-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.

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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

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