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Computational Science Jobs in Texas (NOW HIRING)

ExxonMobil

Computational Scientist

Spring, TX · On-site

Required : • PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field. • Experience in developing, applying, and ...

ExxonMobil

Computational Scientist

Spring, TX · On-site

PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field. * Experience in developing, applying, and analyzing physics-based ...

ExxonMobil

Computational Scientist

Spring, TX · On-site

PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field. * Experience in developing, applying, and analyzing physics-based ...

ExxonMobil

Computational Scientist

Spring, TX

PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field. * Experience in developing, applying, and analyzing physics-based ...

4439

Computational Scientist, BioHPC

Dallas, TX

Education Bachelor's Degree In Computer Science, Engineering, Physics, or other field related to biomedical and computational research Preferred * Education Master's Degree or PhD * Experience ...

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Computational Science information

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$52.6K

$77.4K

$91.3K

How much do computational science jobs pay per year?

As of Jun 27, 2026, the average yearly pay for computational science in Texas is $77,429.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,200.00 and $87,100.00 per year, depending on experience, location, and employer.

What are some common challenges faced by computational scientists when working on interdisciplinary projects?

Computational scientists often collaborate with experts from fields like biology, physics, or engineering, which can present challenges in bridging gaps in domain-specific knowledge and communication styles. Adapting computational models to fit the unique requirements of different disciplines, while ensuring accuracy and efficiency, is a frequent hurdle. Additionally, managing large datasets and integrating diverse computational tools requires strong technical and organizational skills. Open communication and a willingness to learn from colleagues are key to overcoming these challenges and achieving successful project outcomes.

What are the key skills and qualifications needed to thrive as a Computational Scientist, and why are they important?

To thrive as a Computational Scientist, you need a strong background in mathematics, programming (such as Python, C++, or MATLAB), and domain-specific scientific knowledge, often supported by an advanced degree in a relevant field. Familiarity with high-performance computing (HPC) systems, parallel processing frameworks, and scientific data analysis tools is typically required. Excellent problem-solving skills, collaboration, and effective communication set top candidates apart in interdisciplinary research environments. These skills and qualities are crucial for driving innovative scientific discovery and translating complex data into actionable insights.

What is the difference between Computational Science vs Data Scientist?

AspectComputational ScienceData Scientist
Required CredentialsDegree in science, engineering, or computational fields; often requires advanced degreesDegree in statistics, computer science, or related fields; often requires knowledge of programming and analytics
Work EnvironmentResearch labs, universities, industry R&D departmentsTech companies, finance, healthcare, consulting firms
Industry UsageScientific research, simulation, modelingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

Computational Science focuses on developing models and simulations to solve scientific and engineering problems, often requiring advanced degrees and research environments. Data Scientists analyze large datasets to extract insights and support decision-making, typically working in business or tech sectors. While both roles involve programming and data handling, their primary goals and work settings differ significantly.

What can you do with a computational science degree?

A computational science degree prepares individuals for roles such as computational scientist, data analyst, simulation engineer, or research scientist. Graduates often work in industries like healthcare, finance, aerospace, and academia, utilizing skills in programming, modeling, and data analysis to solve complex problems. Knowledge of tools like Python, MATLAB, or high-performance computing environments is also valuable.

What is computational science?

Computational science is an interdisciplinary field that uses advanced computing capabilities to understand and solve complex problems. It combines elements of mathematics, computer science, and domain-specific knowledge to create simulations, analyze data, and model physical, biological, or social systems. Computational scientists develop algorithms and use high-performance computing to tackle problems that are difficult or impossible to solve analytically. This field is essential in areas such as climate modeling, drug discovery, engineering, and physics.

What does a computational scientist do?

A computational scientist develops and applies computer models, algorithms, and simulations to analyze complex scientific problems across fields like physics, biology, and engineering. They often use programming languages, high-performance computing, and data analysis tools to interpret large datasets and support research decisions.

What is computational science salary?

Computational science professionals typically earn a median salary ranging from $70,000 to $120,000 annually, depending on experience, education, and location. Advanced skills in programming, data analysis, and familiarity with scientific software can influence earning potential.

Is computational science a good degree?

Computational science is a valuable degree for careers in research, data analysis, and simulation-based roles across industries such as engineering, finance, and technology. It typically requires strong skills in programming, mathematics, and problem-solving, and can lead to well-paying jobs with opportunities for advancement. The degree prepares students for interdisciplinary work involving scientific computing tools and methods.
What are popular job titles related to Computational Science jobs in Texas? For Computational Science jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Computational Science jobs in Texas look for? The top searched job categories for Computational Science jobs in Texas are:
What cities in Texas are hiring for Computational Science jobs? Cities in Texas with the most Computational Science job openings:
Computational Science jobs near you
Infographic showing various Computational Science job openings in Texas as of June 2026, with employment types broken down into 38% Full Time, 56% Part Time, 4% Contract, and 2% Nights. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $77,429 per year, or $37.2 per hour.
Computational Scientist

Computational Scientist

ExxonMobil

Spring, TX • On-site

Full-time

Posted 22 days ago

ExxonMobil rating

6.1

Company rating: 6.1 out of 10

Based on 221 frontline employees who took The Breakroom Quiz

54th of 74 rated oil and gas companies

Job description

Job Summary:
ExxonMobil is one of the world’s largest publicly traded energy and chemical companies, seeking a highly skilled and motivated Computational Scientist to join their team. This role involves developing and analyzing both physics-based and data-driven computational models to tackle a range of problems in the oil and gas industry.
Responsibilities:
• Work collaboratively across global, cross-disciplinary teams, and with third parties (academia, industry) to assess, accelerate pace of computational science technology development and deployment.
• Frame computational challenge from business needs, develop solutions that strike a balance between accuracy and runtimes, develop solutions that merge physics and data incorporating uncertainty, develop novel approaches to constrain predictive models with field data.
Qualifications:
Required:
• PhD from a recognized university in Engineering, Applied Mathematics, Geoscience, Computational Science, or a closely related field.
• Experience in developing, applying, and analyzing physics-based models and developing related algorithms.
• Strong background in multiscale and/or multiphysics mathematical modeling, scientific computing, and numerical analysis.
• Hands-on experience with deep learning, including familiarity with a range of architectures (e.g., autoencoder, transformer, diffusion model, GAN) and their application to industrial, engineering, or scientific problems.
• Experience in surrogate modeling approaches (e.g., deep learning, machine learning, physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational cost in decision-making processes (e.g., optimization, inverse problems, data assimilation) while maintaining fit-for-purpose accuracy.
• Experience in formulating and solving convex and PDE constrained optimization problems.
• Strong proficiency in programming/scripting languages like Python or C++/C#.
• Proficiency in ML frameworks (PyTorch, TensorFlow, scikit-learn) experience with Databricks/Spark is a plus.
• Experience with software engineering best practices including software testing, agile development, version control, and DevOps.
• Experience working in Linux and High-Performance Computing environment is desirable but not required.
• Prior experience in the upstream oil and gas industry is an advantage.
• Strong communication skills and ability to work effectively in interdisciplinary teams to translate complex computational models into actionable insights.
Company:
ExxonMobil is an international oil and gas company that provides energy that helps underpin growing economies. Founded in 1870, the company is headquartered in Irving, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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