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Agent Based Modeling Scientist Jobs in Texas (NOW HIRING)

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

... process-based ecosystem models. The role plays a critical part in ensuring data quality, reproducibility, and traceability so that scientific outputs can be translated into trusted, credit-grade ...

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Experience implementing generative AI and agent-based systems. * Hands-on experience with ... and model serving. * Experience integrating AI capabilities with Microsoft Copilot platforms.

Kodiak Gas

Full Stack Developer

The Woodlands, TX · On-site

... agent-based automation to deliver scalable, cloud-native business solutions. The developer will ... Develop and maintain data models, semantic layers, and analytics solutions using Power BI and ...

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Experience implementing generative AI and agent-based systems. * Hands-on experience with ... and model serving. * Experience integrating AI capabilities with Microsoft Copilot platforms.

1 point system

Sr. Full-Stack

Houston, TX · On-site

Agent-based architectures / "Agentic AI" * Experience building internal platforms or developer frameworks * Exposure to model management and automation pipelines * Familiarity with memory integration ...

Select Minds LLC

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 ...

PROLIM Global Corporation

Data Scientist

Dallas, TX · On-site

Data Scientist Remote Contract JD: Python Fast API Engineer (ML + Risk Modeling) "Strong hands-on ... Support model hosting & execution for Python-based models and enable flexible deployment patterns ...

Chewy

Senior Data Scientist

Richardson, TX

$109K - $190K/yr

... agent experiences. * Interpret model outcomes, identify key drivers, and clearly communicate ... Ability to work in ambiguity, rapidly test ideas, iterate based on feedback, and move from ...

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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:
Agent Based Modeling Scientist jobs near you
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.

Data Engineer

Arva Intelligence

Houston, TX • On-site, Remote

$95K - $130K/yr

Other

Re-posted 21 days ago

Job description

Job Title:                          Data Engineer 

Department:                     Modeling & Analytics

Reports to:                       Lead Modeling Scientist

Location:                          Remote

Base Salary Range:        $95k - $130k

General Position Description

The Data Engineer is responsible for building and scaling the data and computational backbone that supports Arva's ecosystem modeling and measurement, reporting, and verification platforms. This role sits within a multidisciplinary Data Science team and focuses on designing reliable, auditable, and scalable data systems that enable biogeochemical modeling and optimization at production scale.

In this role, the Data Engineer will design and maintain production-grade data pipelines that integrate diverse datasets including field measurements, management practices, soils, and weather with process-based ecosystem models. The role plays a critical part in ensuring data quality, reproducibility, and traceability so that scientific outputs can be translated into trusted, credit-grade results with real-world impact.

Primary Job Responsibilities

Data Pipeline and Workflow Development

  • Design, implement, and maintain scalable data pipelines supporting ecosystem and biogeochemical modeling
  • Build reproducible workflows that generate standardized model inputs and manage outputs across space, time, and scenario analysis
  • Integrate heterogeneous datasets, including field data, management data, soil data, and weather data, into modeling pipelines

Cloud Infrastructure and Data Systems

  • Develop and maintain cloud-based infrastructure to support modeling pipelines and optimization workflows
  • Implement data storage solutions using relational, spatial, and object-based databases
  • Support efficient data access and processing using platforms such as PostgreSQL, PostGIS, and cloud object storage

Data Quality, Governance, and Auditability

  • Ensure data quality, versioning, traceability, and auditability to support measurement, reporting, and verification requirements
  • Implement validation and monitoring processes to ensure reliability of model inputs and outputs
  • Support transparent, repeatable workflows suitable for regulatory and credit market review

Software Engineering and Collaboration

  • Write clean, modular, and well-documented production code that supports maintainable and scalable data systems
  • Apply software engineering best practices including testing, version control, and documentation
  • Collaborate closely with Data Science and Technology teams to align data infrastructure with modeling, analytics, and production needs

Key Competencies / Requirements

  • 3+ years demonstrated experience building and maintaining data pipelines for large, complex, and heterogeneous datasets
  • Strong proficiency in Python and modern data engineering tools, with experience writing production-grade, testable code
  • Experience working with cloud platforms, with AWS strongly preferred
  • Familiarity with containerization tools such as Docker and version control systems such as GitHub
  • Experience with relational and spatial databases, including PostgreSQL and PostGIS
  • Experience working with geospatial data formats and spatial data processing
  • Experience supporting scientific or ecosystem modeling workflows preferred
  • Familiarity with workflow orchestration tools such as Airflow or Prefect preferred
  • Bachelor's or Master's degree or equivalent experience in Data Engineering, Computer Science, Environmental Informatics, or a related field

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