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Research Scientist Optimization Jobs in Minnesota

Unlike traditional data science roles, this position spans the full AI research and development ... inference optimization. * Experience building and evaluating agentic AI systems, multi-agent ...

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... senior research scientist. * Recent (last ~5 years) representative publications in the relevant ...

Sr Applied Scientist I

Saint Paul, MN · On-site

$118K - $177K/yr

Our optimization and analytics platforms integrate open-source technologies to leverage massive ... Employees in this role drive applied research and development initiatives by integrating deep ...

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Research Scientist Optimization information

What does a research scientist in optimization do?

A Research Scientist in Optimization specializes in developing and applying mathematical techniques to improve processes, systems, or algorithms. Their work often involves formulating optimization problems, designing solutions, and collaborating with engineers or data scientists to implement and test their models. These scientists may work in various industries, such as technology, logistics, finance, or manufacturing, to help organizations make better decisions, save resources, or improve performance. Their daily tasks include conducting experiments, analyzing large datasets, and publishing findings in scientific journals.

What are the key skills and qualifications needed to thrive as a research scientist in optimization?

To excel as a Research Scientist in Optimization, you need a strong background in mathematics, computer science, and optimization theory, often supported by a PhD in a related field. Familiarity with programming languages like Python or MATLAB, optimization libraries (e.g., Gurobi, CPLEX), and experience with data analysis tools are typically required. Critical thinking, creativity, and strong communication skills help in formulating novel approaches and presenting complex findings clearly. These skills drive the development of efficient algorithms and solutions, advancing research impact and innovation in the field.

What types of projects and collaborations can a research scientist in optimization expect to be involved in?

As a Research Scientist specializing in Optimization, you can expect to work on projects that involve developing and improving algorithms to solve complex real-world problems in areas such as logistics, supply chain, or machine learning. Collaboration is common, often involving cross-functional teams with data scientists, software engineers, and domain experts to implement and test optimization solutions. You may also contribute to academic publications, attend conferences, and sometimes mentor junior researchers, all while staying current with the latest advancements in optimization techniques.

What is the difference between Research Scientist Optimization vs Data Scientist?

AspectResearch Scientist OptimizationData Scientist
Required CredentialsMaster's or PhD in Operations Research, Mathematics, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, R&D departments, academiaBusiness analytics, tech companies, consulting firms
Industry UsageOptimization problems, algorithm development, mathematical modelingData analysis, predictive modeling, data visualization

Research Scientist Optimization focuses on developing mathematical models and algorithms to solve complex optimization problems, often in research or academic settings. Data Scientists analyze large datasets to extract insights and build predictive models for business decisions. While both roles require strong analytical skills, Research Scientist Optimization emphasizes mathematical and algorithmic development, whereas Data Scientists focus on data analysis and interpretation.

What job categories do people searching Research Scientist Optimization jobs in Minnesota look for?

The top searched job categories for Research Scientist Optimization jobs in Minnesota are:

What cities in Minnesota are hiring for Research Scientist Optimization jobs?

Cities in Minnesota with the most Research Scientist Optimization job openings:

AI Research Scientist

Minneapolis, MN • On-site


US Bank
Banking and Credit Intermediation • 10K+ employees

8.2

Company rating: 8.2 out of 10

Based on 362 frontline employees who took The Breakroom Quiz

52nd of 172 rated banks

People enjoy working here

Good employer

Recommended by students


Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago


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

U.S. Bank is seeking an AI Scientist to join the Artificial Intelligence Center of Excellence (AI CoE), a high-impact organization responsible for advancing the bank's AI strategy through applied research, innovation, rapid prototyping, and enterprise deployment.

This role is ideal for a highly technical and hands-on AI practitioner who thrives at the intersection of research, experimentation, and implementation. The successful candidate will continuously evaluate emerging advances in artificial intelligence, identify opportunities to create business value, rapidly prototype novel solutions, and help evolve successful concepts into scalable enterprise capabilities.

Unlike traditional data science roles, this position spans the full AI research and development lifecycle. The ideal candidate combines strong scientific and engineering expertise with a practical mindset, enabling them to move seamlessly from exploratory research and experimentation to the development and deployment of production-grade AI solutions.

The candidate is expected to remain actively engaged with the broader AI community, stay current on academic and industry developments, and contribute to advancing AI innovation within the bank.

Key ResponsibilitiesAI Research & Innovation
  • Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems.

  • Identify opportunities to apply advanced AI techniques to complex business problems across financial services.

  • Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches.

  • Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and business stakeholders.

  • Contribute to patents, technical publications, whitepapers, prototypes, and innovation initiatives.

Prototyping & Solution Development
  • Rapidly transform research concepts into working prototypes and proof-of-concepts.

  • Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring.

  • Build experimental and production-ready solutions using modern AI/ML tools, frameworks, and cloud platforms.

  • Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.

Generative AI & Agentic Systems
  • Develop solutions leveraging foundation models, generative AI, retrieval-augmented generation (RAG), fine-tuning techniques, and agentic workflows.

  • Design and evaluate AI agents, multi-agent systems, orchestration frameworks, tool-use architectures, memory systems, and human-in-the-loop workflows.

  • Contribute to best practices for prompt engineering, model adaptation, evaluation, observability, and governance of LLM-based systems.

  • Assess emerging model architectures and determine their applicability within a highly regulated environment.

Deployment & Technical Collaboration
  • Partner with software engineers, platform teams, product managers, and business stakeholders to transition successful prototypes into production environments.

  • Contribute to deployment and operationalization efforts for AI solutions.

  • Help balance innovation, scalability, security, compliance, and operational requirements throughout solution development.

  • Share knowledge and provide technical guidance to peers and junior team members.

  • Take ownership of assigned initiatives and ensure successful delivery of AI capabilities from concept through deployment.

Basic Qualifications

  • Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience
  • Eight or more years of relevant experience
Preferred Qualifications
  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Linguistics, or a related field strongly preferred.

  • Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.

  • Experience with generative AI technologies, including LLMs, fine-tuning, RAG systems, model evaluation, and inference optimization.

  • Experience building and evaluating agentic AI systems, multi-agent workflows, AI orchestration frameworks, and autonomous decision-making architectures.

  • Hands-on experience with PyTorch, Hugging Face, LangChain, LangGraph, or equivalent AI ecosystems.

  • Demonstrated record of innovation through publications, patents, open-source contributions, conference presentations, or impactful AI solution delivery.

  • Experience developing AI solutions within highly regulated industries such as financial services, healthcare, insurance, or telecommunications.

  • Strong communication skills and the ability to translate complex AI concepts into actionable business outcomes.

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.


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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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What U.S. Bank employees say

Pay

Benefits

Hours and flexibility

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