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Remote Computational Engineering Jobs in Hawaii (NOW HIRING)

Remote Computational Engineering information

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

To thrive as a Remote Computational Engineer, you need strong analytical and mathematical abilities, proficiency in computational modeling, and a degree in engineering, mathematics, or a related field. Familiarity with programming languages (such as Python, MATLAB, or C++), high-performance computing systems, and relevant simulation software is typically required. Excellent problem-solving, self-motivation, and clear communication skills help you collaborate effectively in a remote environment. These skills ensure that you can develop accurate models, contribute to complex projects, and maintain productivity while working independently.

How does a remote computational engineer typically collaborate with team members on complex projects?

Remote computational engineers often use collaborative software tools, such as version control systems, cloud-based simulation platforms, and video conferencing, to stay connected with their teams. They regularly participate in virtual meetings, share project updates, and review code or modeling results together. Despite working remotely, strong communication skills are essential to coordinate with multidisciplinary teams, address technical challenges, and ensure alignment on project goals and deadlines.

What is remote computational engineering?

Remote computational engineering involves using computer-based simulations and modeling tools to solve engineering problems from a remote location, rather than working onsite. Professionals in this field apply advanced mathematics, physics, and programming to design, analyze, and optimize systems or products. They often collaborate with teams virtually and use software to perform tasks such as finite element analysis (FEA), computational fluid dynamics (CFD), or algorithm development. This role enables flexibility in work location while contributing to innovative engineering projects across various industries.

What is the difference between Remote Computational Engineering vs Remote Data Scientist?

AspectRemote Computational EngineeringRemote Data Scientist
Required CredentialsBachelor's or higher in engineering, computer science, or related fields; programming skillsBachelor's or higher in statistics, computer science, or related fields; programming and statistical skills
Work EnvironmentCollaborative engineering teams, simulation labs, software developmentData analysis teams, research environments, analytics platforms
Industry UsageEngineering firms, tech companies, manufacturing
Common Search IntentComparing roles in engineering and technical development

Remote Computational Engineering and Remote Data Scientist roles share a focus on programming and analytical skills, often requiring similar educational backgrounds. However, computational engineers typically work on simulations, modeling, and engineering solutions, while data scientists focus on analyzing data to derive insights. Both roles are prevalent in tech-driven industries and often involve remote collaboration, but their core functions differ in application and industry focus.

What job categories do people searching Remote Computational Engineering jobs in Hawaii look for? The top searched job categories for Remote Computational Engineering jobs in Hawaii are:
What cities in Hawaii are hiring for Remote Computational Engineering jobs? Cities in Hawaii with the most Remote Computational Engineering job openings:
Infographic showing various Remote Computational Engineering job openings in Hawaii as of May 2026, with employment types broken down into 53% Full Time, and 47% Part Time. Highlights an 8% Physical, 17% Hybrid, and 75% Remote job distribution.
Computational Physicist - AI Trainer

Computational Physicist - AI Trainer

DataAnnotation

Honolulu, HI • On-site, Remote

$40/hr

Full-time

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


Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr