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Remote Mathematical Engineer Jobs in Utah (NOW HIRING)

SAIC

Mechanical Engineer

Hill Air Force Base, UT · On-site +1

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an exceptional Mechanical ... Bachelor's degree in mechanical engineering, Systems Engineering, Physics, or Mathematics with 5+ ...

Ovivo

Product Engineer - E2METRIX

Salt Lake City, UT · Remote

The role is based in our Salt Lake City Office, but can be fully remote. If in Salt Lake City, you ... Ability to apply advanced mathematical equations to complex situations. Don't meet every single ...

DataAnnotation

Physicist - AI Trainer

Salt Lake City, UT · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus ...

DataAnnotation

Data Science Consultant

Salt Lake City, UT · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus ...

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Remote Mathematical Engineer information

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

To thrive as a Remote Mathematical Engineer, you need a strong background in advanced mathematics, problem-solving, and programming, typically with a degree in mathematics, engineering, or a related field. Familiarity with tools like MATLAB, Python, R, and mathematical modeling software, as well as experience with version control systems such as Git, is important. Strong analytical thinking, self-motivation, and effective remote communication skills help you excel in collaborative and independent work environments. These competencies ensure you can develop, implement, and communicate complex mathematical solutions for real-world problems while effectively collaborating across distributed teams.

How do Remote Mathematical Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Mathematical Engineers often work closely with software developers, data scientists, and project managers using collaborative tools like video conferencing, shared code repositories, and project management platforms. Regular virtual meetings help ensure alignment on project goals and allow for real-time problem-solving. Effective communication and documentation skills are essential, as much of the collaboration happens asynchronously. Building strong relationships with team members and proactively sharing progress updates are key to thriving in this remote, team-oriented environment.

What is a Remote Mathematical Engineer?

A Remote Mathematical Engineer is a professional who applies advanced mathematical theories, techniques, and computational methods to solve complex problems in various fields, such as engineering, finance, technology, and data science, while working from a remote location. They often develop algorithms, create mathematical models, and analyze data to support decision-making or product development. Remote roles allow these engineers to collaborate with teams and clients online, using specialized software and communication tools. This position typically requires strong analytical skills, proficiency in mathematics and programming, and the ability to work independently.

What is the difference between Remote Mathematical Engineer vs Remote Data Scientist?

AspectRemote Mathematical EngineerRemote Data Scientist
Required CredentialsMathematics, Engineering, or related technical degrees; strong analytical skillsStatistics, Computer Science, or related degrees; data analysis expertise
Work EnvironmentCollaborates with engineering teams on algorithm development and modelingAnalyzes data to extract insights, builds predictive models
Employer & Industry UsageTech, finance, aerospace, research institutionsTech companies, finance, healthcare, consulting
Search & Comparison IntentFocuses on mathematical modeling and engineering solutionsFocuses on data analysis and machine learning applications

Remote Mathematical Engineers primarily develop mathematical models and algorithms for engineering problems, often working closely with technical teams. Remote Data Scientists analyze large datasets to generate insights and predictive models. While both roles require strong analytical skills and technical backgrounds, their focus areas differ: engineering solutions versus data analysis.

What are the most commonly searched types of Mathematical Engineer jobs in Utah? The most popular types of Mathematical Engineer jobs in Utah are:
What are popular job titles related to Remote Mathematical Engineer jobs in Utah? For Remote Mathematical Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Remote Mathematical Engineer jobs in Utah look for? The top searched job categories for Remote Mathematical Engineer jobs in Utah are:
What cities in Utah are hiring for Remote Mathematical Engineer jobs? Cities in Utah with the most Remote Mathematical Engineer job openings:
Remote Mathematical Engineer jobs near you
Remote Analytics Engineer & AI Trainer

Remote Analytics Engineer & AI Trainer

DataAnnotation

Salt Lake City, UT • On-site, Remote

$60/hr

Full-time

Posted 18 days ago

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, up to $60 USD/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

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