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Remote Ai Computer Science Jobs in Arizona (NOW HIRING)

DataAnnotation

Economist - AI Trainer

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 ...

DataAnnotation

Physicist - AI Trainer

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 ...

DataAnnotation

Economic Analyst - AI Trainer

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 ...

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 ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

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

To thrive as a Remote AI Computer Scientist, you need a strong background in computer science, programming (Python, Java, or C++), and a solid understanding of machine learning algorithms, typically supported by a degree in computer science or a related field. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms, and relevant certifications like TensorFlow Developer or AWS Certified Machine Learning are common technical requirements. Excellent problem-solving skills, self-motivation, and effective remote communication are soft skills that set top performers apart. These abilities are critical for developing innovative AI solutions, collaborating with distributed teams, and adapting to rapidly changing technology landscapes.

What are the typical collaboration methods for remote AI Computer Science professionals working on team projects?

Remote AI Computer Science professionals often collaborate using a combination of cloud-based code repositories, video conferencing, and project management tools. Teams typically hold regular virtual stand-ups, code review sessions, and brainstorming meetings to ensure alignment and knowledge sharing. Effective communication and documentation are crucial, as team members may be in different time zones. Additionally, pair programming and collaborative debugging sessions are common practices to maintain code quality and foster team cohesion.

What is a remote AI computer science job?

A remote AI computer science job involves working from a location outside a traditional office—often from home—on tasks related to artificial intelligence and computer science. Professionals in this role typically develop, test, and deploy AI models, analyze large datasets, and write code to solve complex problems. They may collaborate with teams using online tools and are expected to stay updated on the latest AI technologies and programming languages. This job can be found in industries ranging from tech startups to large corporations, and offers flexibility in work schedule and location.
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Remote Ai Computer Science jobs near you
Economist - AI Trainer

Economist - AI Trainer

DataAnnotation

Phoenix, AZ • On-site, Remote

$40/hr

Full-time

Posted 17 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, 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

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