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Agent Based Modeling Scientist Jobs in Minnesota

CSAA

This Data Scientist role offers the opportunity to help CSAA Insurance Group anticipate and prepare ... Lead the design, development, and validation of simulation models (discrete-event, agent-based ...

Royal Bank of Canada

Agent Lead

Minneapolis, MN · On-site

Model risk governance * Data privacy and security requirements * AI explainability and control ... Familiarity with CRM-based agent platforms (e.g., Salesforce Agentforce) * Exposure to event-driven ...

Royal Bank of Canada

Agent Lead

Minneapolis, MN · On-site

Model risk governance * Data privacy and security requirements * AI explainability and control ... Familiarity with CRM-based agent platforms (e.g., Salesforce Agentforce) * Exposure to event-driven ...

US Bank

AI Research Scientist

Minneapolis, MN · On-site

Design and evaluate AI agents, multi-agent systems, orchestration frameworks, tool-use ... based systems. * Assess emerging model architectures and determine their applicability within a ...

U.S. Bank

AI Research Scientist

Minneapolis, MN · On-site

Design and evaluate AI agents, multi-agent systems, orchestration frameworks, tool-use ... based systems. * Assess emerging model architectures and determine their applicability within a ...

UnitedHealth Group

Senior AI/ML Engineer

Eden Prairie, MN · On-site

$106K - $146K/yr

We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for healthcare. We ... You will work on large language models, retrieval-augmented generation pipelines, and agent-based ...

US Bank

AI Scientist

Minneapolis, MN · On-site

Design and evaluate AI agents, multi-agent systems, orchestration frameworks, tool-use ... based systems. * Assess emerging model architectures and determine their applicability within a ...

Target

Sr Engineer - Agentic Data Platform

Minneapolis, MN · On-site +1

$98K - $176K/yr

You will work across agent orchestration, data and metadata access, semantic models, evaluation ... MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related ...

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Agent Based Modeling Scientist information

What is an agent based modeling scientist?

An Agent Based Modeling (ABM) Scientist is a researcher or professional who develops computational models that simulate the actions and interactions of autonomous agents (such as individuals, groups, or entities) to study complex systems. These scientists use ABM techniques to analyze how the behavior of individual agents leads to collective outcomes, often in fields like biology, economics, social sciences, and epidemiology. Their work involves designing models, running simulations, and interpreting data to gain insights into system dynamics and emergent phenomena.

How does an agent based modeling scientist typically collaborate with interdisciplinary teams during a project?

Agent Based Modeling Scientists often work closely with experts from fields such as economics, epidemiology, engineering, and computer science to ensure that models accurately reflect real-world systems. Collaboration usually involves regular meetings to define system parameters, validate model assumptions, and interpret simulation results. Effective communication is essential, as team members may not always be familiar with agent-based modeling concepts. Sharing insights and translating technical findings for broader audiences helps ensure models are both robust and actionable for decision-makers.

What are the key skills and qualifications needed to thrive as an agent based modeling scientist, and why are they important?

To thrive as an Agent Based Modeling Scientist, you need expertise in computational modeling, systems theory, and a strong background in mathematics or related fields, often supported by an advanced degree. Proficiency with programming languages such as Python, Java, or NetLogo and familiarity with simulation software are typically required. Analytical thinking, problem-solving, and the ability to communicate complex concepts clearly are valuable soft skills in this role. These skills are crucial for accurately developing, interpreting, and conveying insights from agent-based models to inform research or decision-making.

What is the difference between Agent Based Modeling Scientist vs Data Scientist?

AspectAgent Based Modeling ScientistData Scientist
Required CredentialsMaster's or PhD in computer science, mathematics, or related fields; experience with modeling and simulationDegree in statistics, computer science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentResearch labs, academia, or industry focused on simulation and modeling projectsBusiness, tech companies, or consulting firms analyzing large datasets
Industry UsageResearch, simulation, complex systems modelingData analysis, predictive modeling, business insights

While both roles require strong analytical skills and programming knowledge, an Agent Based Modeling Scientist specializes in creating simulations of autonomous agents within complex systems, whereas a Data Scientist focuses on analyzing and interpreting large datasets to inform business decisions.

What are popular job titles related to Agent Based Modeling Scientist jobs in Minnesota?

For Agent Based Modeling Scientist jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Agent Based Modeling Scientist jobs in Minnesota look for?

The top searched job categories for Agent Based Modeling Scientist jobs in Minnesota are:

What cities in Minnesota are hiring for Agent Based Modeling Scientist jobs?

Cities in Minnesota with the most Agent Based Modeling Scientist job openings:

Agent Based Modeling Scientist jobs near you
Infographic showing various Agent Based Modeling Scientist job openings in Minnesota as of July 2026, with employment types broken down into 1% Locum Tenens, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.

Data Scientist, Principal - AI Product Engineering (Minneapolis)

Blue Shield of CA

Minneapolis, MN • On-site

Full-time

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

Job description

Your Role

The AI & Machine Learning team works in partnership across the enterprise to accelerate business outcomes by applying AI, machine learning, and generative AI to build intelligent products that create intelligence at scale. Reporting to the Director, AI & Machine Learning, the Data Scientist, Principal will lead the development and deployment of novel applications that leverage generative AI models. This role focuses on rapidly developing new features and working across partner teams to deliver solutions and maximize impact, translating cutting-edge AI research into real-world products and taking features from 0 to 1. You will design, build, and ship production-grade AI products including LLM-powered applications, AI agents and copilots, retrieval-augmented generation (RAG) and search, and AI-enabled automation embedded directly into customer-facing applications and enterprise workflows such as claims, payment integrity, clinical insights, and member experience. You will set the technical direction for how AI is applied across the organization.

Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Your Knowledge and Experience
  • Bachelor's degree in computer science, a quantitative discipline, or equivalent practical experience; Master's degree or PhD preferred
  • 10 years of prior relevant experience in data science, machine learning, applied AI/ML, software engineering, or advanced analytics
  • Proven track record of building and shipping software products rapidly, not just developing models or analyses
  • Strong software engineering skills and proficiency in Python, including building APIs and backend services
  • Experience leading ML design and optimizing ML infrastructure, model deployment, evaluation, and data processing, and working with machine learning frameworks and libraries
  • Hands-on experience with deep learning and LLM application frameworks, including PyTorch, TensorFlow, LangChain, and LangGraph
  • Hands-on experience building applications that leverage generative AI models, including prompt engineering and retrieval-augmented generation (RAG)
  • Experience with generative AI research or applications preferred
  • Experience designing agent-based systems and orchestration frameworks preferred
  • Experience with cloud computing platforms and infrastructure (e.g., Azure, Google Cloud, or AWS), and scalable data processing with SQL or Spark preferred
  • Solid MLOps and LLMOps practices, including CI/CD, monitoring, and model lifecycle management preferred
  • Experience rapidly developing and shipping software in a fast-paced, customer-facing environment, adapting to changing priorities preferred
  • Understanding of responsible AI and governance for regulated or healthcare environments preferred
Hybrid

This role requires employees to be in-office based on our hybrid workplace model, balancing purposeful in-person collaboration with flexibility. For most teams, this means coming into the office two days each week.

Employees living more than 50 miles from an office location will work with their manager to determine in-office time based on business need.

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