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Agent Based Modeling Scientist Jobs in Texas (NOW HIRING)

... and Agent based modeling using tools such as Anylogic * MS or BS in Computer Science,Math, Physics, Information Science, Engineering or other related field Skills * Experience in digital twin ...

... and Agent based modeling using tools such as AnyLogic * MS or BS in Computer Science, Math, Physics, Information Science, Engineering or other related field Skill * Experience in digital twin ...

Senior Staff Agentic AI Engineer

Frisco, TX · On-site +1

$99K - $134K/yr

Bachelor's Degree in Computer Science or related field of study. * 12+ years of experience in ... Agent Based Modeling * Amazon Web Services (AWS) * Datadog * OpenAI * Grafana * Graph Databases

Sr Data Scientist GenAI

Dallas, TX · On-site

$150K - $210K/yr

... models (vision + text) or emerging LLMs and agent-based systems. - Experience with open source LLMs & toolkits; familiarity with LangChain or similar frameworks. - Prior experience in regulated ...

Sr Data Scientist GenAI

Dallas, TX · On-site +1

$150K - $210K/yr

... models (vision + text) or emerging LLMs and agent-based systems. - Experience with open source LLMs & toolkits; familiarity with LangChain or similar frameworks. - Prior experience in regulated ...

Drive technical excellence in model evaluation, interpretability, robustness, performance tuning ... Proficiency with GenAI agents, including designing, orchestrating, or deploying agent-based AI ...

You will also mentor engineers who want to learn AI, LLMs, and agent-based development, fostering a ... Establish and model engineering best practices for reliability, interpretability, safety ...

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 ...

Lead AI Engineer

Irving, TX · On-site

$156K - $234K/yr

Architect advanced agent-based systems (perception, reasoning, planning, execution), integrating ... Nice to Have Advanced data science expertise (statistical modeling, experimentation). Demonstrated ...

The Director, Data Science will lead efforts across personalization, recommendation systems, and ... agent integration with enterprise systems and external tools. * Apply transformer-based models ...

Agentic AI Engineer

Dallas, TX · On-site

$120K - $140K/yr

... Models (LLMs), and AI orchestration frameworks to design and develop enterprise-grade AI ... Design, develop, and deploy agent-based AI applications using LangGraph, LangChain, and similar ...

... models, predictive and prescriptive analytics, and end-to-end, multi-agent systems in support of ... tree-based models, and anomaly detection. * Understanding of applied statistics and statistical ...

... models, predictive and prescriptive analytics, and end-to-end, multi-agent systems in support of ... tree-based models, and anomaly detection. * Understanding of applied statistics and statistical ...

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Agent Based Modeling Scientist information

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 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.

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 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.
What are popular job titles related to Agent Based Modeling Scientist jobs in Texas? For Agent Based Modeling Scientist jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Agent Based Modeling Scientist jobs in Texas look for? The top searched job categories for Agent Based Modeling Scientist jobs in Texas are:
What cities in Texas are hiring for Agent Based Modeling Scientist jobs? Cities in Texas with the most Agent Based Modeling Scientist job openings:
Infographic showing various Agent Based Modeling Scientist job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Simulation engineer

InfoVision, Inc.

Irving, TX • On-site

Other

Re-posted 6 days ago


Job description

Experience   

  • 5+ years experience in designing  and developing enterprise level digital twin modeling, simulation, optimization solutions
  • 3+ years with System dynamics, Discrete events and Agent based modeling using tools such as Anylogic
  • MS or BS  in Computer Science,Math, Physics, Information Science, Engineering or other related field

Skills

  • Experience in digital twin modeling, simulation, optimization using anylogic Matlab etc             
  • Experience/ familiarity in building and engineering digital twins solutions with simulation technique
  • Knowledge of Artificial Intelligence and machine learning (AI/ML) techniques
  • Experience in data driven approach to analyze problems and deliver robust, optimized solution
  • Experience with various database technologies like RDBMS, Big Data Technologies
  • Experience with Java, Python, C++
  • Experience working with BI tools like Tableau, Looker, Qlik, etc..
  • Experience in building, hosting applications in Google Cloud Platform kubernetes is a plus.
  • Familiarity with IoT understanding from connectivity and data management perspective
  • Knowledge of architecting and managing end to end solutions and perform root cause analysis