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Remote Computer Science Jobs in Herriman, UT (NOW HIRING)

System One

IBM Data Stage Engineer

Cottonwood Heights, UT · Remote

$108.70K - $130.50K/yr

Salt Lake City , UT OR Remote a Possibility Duration - Contract -to-Hire Required qualifications to be successful in this role . Bachelor''s degree in Computer Science, Engineering, Information ...

NICE

IT Technical Support

Sandy, UT · On-site +1

$20.50 - $28/hr

Excellent Customer Service skills and must be able to work alone and with remote teams. Education: Degree in Computer Science or Information Technology - Desired (Or Equivalent work experience ...

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What Are Remote Computer Science Jobs?

Remote computer science jobs include a wide variety of roles focused on the use and analysis of computers and networks, including security specialists, network administrators, and software programmers. In these roles, you may develop hardware or software, control user accounts and permissions, analyze security procedures, manage confidential information, order repairs and replacements, manage inventory levels, conduct penetration tests, or manage a full development cycle for new software. Remote computer science jobs frequently use databases, private networks, intrusion detection systems, and remote conferencing software to help coordinate jobs. This is something of a catch-all term for computer-based positions, so if you are looking for a specific role, such as a remote programmer or remote computer engineer, you may need to narrow your search terminology.

What are the key skills and qualifications needed to thrive as a Remote Computer Science professional, and why are they important?

To thrive as a Remote Computer Science professional, you need strong programming skills, problem-solving abilities, and a relevant degree or equivalent experience in computer science or software engineering. Proficiency with coding languages (such as Python, Java, or C++), version control systems like Git, and remote collaboration tools (e.g., Slack, Jira, Zoom) is essential. Excellent communication, self-motivation, and time management are vital soft skills for working independently and with distributed teams. These skills and qualities enable efficient development, seamless teamwork, and successful project delivery in a remote environment.

How do remote computer science professionals typically collaborate with their teams to ensure project success?

Remote computer science professionals usually rely on a mix of communication and project management tools—such as Slack, Zoom, GitHub, and Jira—to collaborate effectively with their teams. Regular virtual meetings, code reviews, and shared documentation help maintain alignment and transparency. While working remotely offers flexibility, it can also require proactive communication and self-management to avoid misunderstandings and stay on track with deliverables. Many teams adopt Agile methodologies to structure their work and foster collaboration, regardless of physical location.
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AI Quant Analyst & Model Trainer Remote

AI Quant Analyst & Model Trainer Remote

DataAnnotation

Salt Lake City, UT • On-site, Remote

$60/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, 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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