ZipRecruiter

Log In

2

Remote Co Op Computer Science Jobs in Phoenix, AZ

DataAnnotation

Decision Scientist

Phoenix, AZ · On-site +1

$40/hr

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

SynergisticIT

Data Scientist

Tempe, AZ · On-site +1

With remote work and global talent pools, even entry-level roles receive hundreds of applications ... Recent graduates in Computer Science, Engineering, Math, Statistics, or related STEM fields

Relativity

Senior Applied Scientist

Phoenix, AZ · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry ...

next page

Showing results 1-20

People also search for

All JobsRemote Co Op Computer Science JobsRemote Co Op Computer Science Jobs in Phoenix, AZ

Remote Co Op Computer Science information

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

To thrive as a Remote Co-Op Computer Science student, you need a solid grasp of programming fundamentals, data structures, algorithms, and typically be pursuing or have completed coursework toward a computer science degree. Familiarity with version control systems like Git, collaborative platforms such as GitHub or Jira, and exposure to coding languages like Python, Java, or C++ are commonly expected. Strong communication, self-motivation, and time management are essential soft skills for remote teamwork and independent learning. These skills ensure you can effectively contribute to projects, adapt to remote workflows, and maximize your experiential learning.

How do Remote Co-Op Computer Science roles typically facilitate mentorship and team collaboration despite the virtual setting?

Remote Co-Op Computer Science positions often leverage various collaboration tools such as Slack, Microsoft Teams, and Zoom to foster communication and mentorship. You'll participate in regular virtual stand-ups, code reviews, and project meetings, ensuring you stay connected with your team and receive guidance from senior engineers. Many companies assign a dedicated mentor or buddy to help you navigate both technical challenges and company culture. This structure allows you to build relationships, gain feedback, and make meaningful contributions without being onsite.

What is a Remote Co-Op in Computer Science?

A Remote Co-Op in Computer Science is a paid or unpaid work placement that allows students to gain real-world experience in their field while working from a location outside the traditional office, such as their home. These positions are typically part of a college or university's cooperative education program, blending academic learning with practical work experience. Students work on software development, data analysis, or IT projects under the supervision of professionals, helping them build technical skills and professional networks. Remote Co-Ops offer flexibility and can connect students with companies outside their local area, broadening their career opportunities.

What is the difference between Remote Co Op Computer Science vs Remote Software Intern?

AspectRemote Co Op Computer ScienceRemote Software Intern
CredentialsTypically enrolled in a computer science program, may require coursework or enrollment verificationUsually students pursuing a degree in computer science or related field, may need proof of enrollment
Work EnvironmentRemote, collaborative team settings, often part-time during academic termsRemote, project-based tasks, often part-time or summer internships
Employer & Industry UsageUsed by tech companies, startups, and corporations for student talent pipelinesCommonly offered by tech firms, startups, and software companies for skill development

Both roles are designed for students gaining practical experience in computer science. The main difference lies in the stage of education and the program structure: Co Op positions are typically part of a formal cooperative education program, while Software Internships are often summer or short-term roles. Both provide valuable industry exposure and skill development in remote settings.

What are popular job titles related to Remote Co Op Computer Science jobs in Phoenix, AZ? For Remote Co Op Computer Science jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Remote Co Op Computer Science jobs in Phoenix, AZ look for? The top searched job categories for Remote Co Op Computer Science jobs in Phoenix, AZ are:
Remote Co Op Computer Science jobs near you
Infographic showing various Remote Co Op Computer Science job openings in Phoenix, AZ as of May 2026, with employment types broken down into 4% As Needed, 48% Full Time, 44% Part Time, and 4% Contract. Highlights an 77% Physical, 1% Hybrid, and 22% Remote job distribution.
Computational Scientist - AI Trainer

Computational Scientist - AI Trainer

DataAnnotation

Phoenix, AZ • 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

Apply