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How much do computational economics jobs pay per hour?

As of May 31, 2026, the average hourly pay for computational economics in the United States is $65.38, according to ZipRecruiter salary data. Most workers in this role earn between $59.62 and $71.15 per hour, depending on experience, location, and employer.

What is a Computational Economics job?

A Computational Economics job involves using mathematical models, simulations, and data analysis techniques to study economic systems and solve complex economic problems. Professionals in this field apply computational methods, including machine learning, optimization, and agent-based modeling, to analyze markets, forecast trends, and evaluate policies. They often work in academia, finance, government, or technology sectors, leveraging programming and statistical tools like Python, R, and MATLAB.

What are the key skills and qualifications needed to thrive in the Computational Economics position, and why are they important?

To thrive in Computational Economics, you need a strong background in economics, mathematics, and computer science, often supported by a degree in economics, statistics, or a related quantitative field. Familiarity with programming languages such as Python, R, or MATLAB, and experience with econometric and data analysis software are typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex findings clearly make candidates stand out. These skills are crucial for building and interpreting economic models, analyzing large datasets, and delivering actionable insights in a collaborative research or business environment.

What are some of the main challenges faced by Computational Economists in their daily work?

Computational Economists often encounter challenges related to handling large and complex datasets, ensuring data quality, and constructing accurate models that capture real-world economic phenomena. Balancing theoretical economic principles with practical computational techniques can also be demanding. Collaborating effectively with multidisciplinary teams, such as data scientists, policy analysts, or business professionals, is vital to translate technical results into actionable recommendations. Adapting to rapidly evolving software tools and staying current with industry best practices are also important aspects of the role.

What is the highest paid job in economics?

The highest paid jobs in economics are often executive roles such as Chief Economist or Director of Economic Research, typically found in finance, consulting, or government sectors. These positions require advanced degrees, strong analytical skills, and extensive experience, with salaries often exceeding six figures annually.
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Computational Economics jobs near you
Infographic showing various Computational Economics job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $135,999 per year, or $65.4 per hour.

Materials Analysis Engineer - Computational and Modeling Focus

Vulcan Elements

Durham, NC

Full-time

Posted 24 days ago

Job description

About Vulcan Elements

Vulcan Elements is manufacturing American rare-earth permanent magnets for a secure, resilient future. With a focus on national security and economic resiliency, we serve critical industries such as defense, aerospace, and automotive powering a high-technology future. Vulcan Elements is building a team of ambitious professionals committed to Mission Focus, Technical Excellence and Transparency.

As a Materials Analysis Engineer – Computational and Modeling Focus, you will utilize modeling and computational tools to support the development and optimization of materials and processes for rare-earth permanent magnet manufacturing. You will routinely work as part of cross-functional teams to support R&D and manufacturing operations, applying simulation and analysis techniques to solve complex materials engineering challenges.


Responsibilities
  • Develop and execute computational models and simulations to support materials development and process optimization, including atomic simulations, phase field modeling, density functional theory (DFT), and finite element analysis (FEA).
  • Apply materials and process modeling techniques to evaluate and improve manufacturing processes for NdFeB permanent magnets.
  • Collaborate with cross-functional teams across R&D, manufacturing, and quality to translate modeling insights into actionable process improvements.
  • Perform and interpret results from materials analytical methods such as electron microscopy, metallography, and chemical analysis to validate and inform computational models.
  • Leverage machine learning tools and data-driven approaches for the analysis and exploration of material properties and process–property relationships.
  • Develop and maintain simulation workflows using tools such as ANSYS and other relevant computational packages.
  • Communicate findings through technical reports, presentations, and publications as appropriate.
  • Stay current with advances in computational materials science and identify opportunities to apply emerging methods to company objectives.

Responsibilities and tasks outlined are not exhaustive and may change as determined by the needs of the business

Qualifications
  • Bachelor's degree or higher in materials science, materials engineering, or metallurgy. Closely related fields may be considered for exceptional candidates.
  • Solid understanding of fundamental materials properties, behavior, diffusion, and phase transformations.
  • Demonstrated experience using one or more of the following for materials analysis or design simulations: atomic simulations, phase field modeling, density functional theory, or finite element analysis.

Must be a U.S. Person due to required access to U.S. export-controlled information or facilities.

Desired Skills
  • Hands-on experience with materials analytical methods such as electron microscopy, metallography, and chemical analysis.
  • Experience using machine learning tools for analysis and exploration of material properties.
  • Experience applying materials and process modeling in a manufacturing or industrial setting.
  • Familiarity with a variety of analyses and packages within ANSYS.
  • Experience performing density functional theory (DFT) calculations.