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Flexible Data Annotation Analyst Jobs in Arizona

YO AI Labs

AI Data Scientist Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Analytical Reasoning * Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical & Report Writing * Content Review & Editing * Data Annotation * Data ...

YO AI Labs

AI Data Science Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Analytical Reasoning * Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical Documentation * Technical & Report Writing * Content Review & Editing * Data Annotation * Data ...

YO AI Labs

AI Finance Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Financial Analysis * Technical & Report Writing * Business Communication * Content Review & Editing * Fact Checking * Data Interpretation * Data Annotation * Problem-Solving * Independent Research

YO AI Labs

AI Consulting Expert - Remote

Phoenix, AZ · Remote

$100 - $200/hr

Data Annotation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail ... Excellent critical thinking, analytical reasoning, and structured problem-solving abilities.

PhoenixNAP

Be Seen First

Senior Asset Management Analyst

Phoenix, AZ · On-site

$87K - $115K/yr

The Senior Asset Management Analyst role involves the purchasing, inventory, tracking and ... The company employs a unique approach to providing flexible data center solutions that are tailored ...

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Flexible Data Annotation Analyst information

What is a flexible data annotation analyst?

A Flexible Data Annotation Analyst is a professional responsible for labeling, categorizing, and tagging data—such as text, images, audio, or video—to prepare it for use in machine learning and artificial intelligence projects. The 'flexible' aspect typically means the role allows for remote work, adjustable hours, or project-based assignments. Analysts use specific tools and follow detailed guidelines to ensure data quality and consistency. This role is crucial for training accurate AI models, as well-annotated data helps improve the performance of automated systems.

What are the key skills and qualifications needed to thrive as a flexible data annotation analyst?

To thrive as a Flexible Data Annotation Analyst, you need keen attention to detail, analytical thinking, and a basic understanding of data labeling processes, often supported by a high school diploma or relevant experience. Familiarity with annotation tools such as Labelbox, Prodigy, or similar platforms, as well as basic proficiency in spreadsheet software, is typically required. Strong time management, adaptability, and clear communication skills help you deliver accurate results and work effectively with remote teams. These abilities ensure high-quality, consistent data labeling that is critical for training reliable machine learning models.

How does a flexible data annotation analyst typically collaborate with other teams to ensure data quality?

As a Flexible Data Annotation Analyst, you will frequently interact with data scientists, machine learning engineers, and project managers to clarify annotation guidelines and resolve ambiguities in the data. Collaboration often involves participating in virtual meetings, providing feedback on annotation tools, and reporting inconsistencies or uncertainties encountered during the labeling process. This teamwork ensures that annotated datasets meet project standards and contribute to high-quality machine learning outcomes. Regular communication and openness to feedback are key to success in this collaborative environment.

Can I work as a flexible data annotation analyst with no experience?

Flexible data annotation analyst roles often do not require prior experience, as training is typically provided to teach the necessary skills and tools. Basic computer literacy and attention to detail are usually sufficient to start, making it accessible for beginners interested in data labeling tasks.

Do data annotation jobs offer flexible hours?

Data annotation jobs often offer flexible hours, allowing workers to choose when they complete tasks, especially in freelance or remote roles. However, some positions may have deadlines or specific schedules depending on the employer or project requirements.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are close to minimum wage or slightly above, depending on the platform and complexity of tasks. Pay rates can vary based on experience, skill level, and the employer, but generally, it is not considered a high-paying role. Many positions are freelance or part-time, which can impact overall earnings.

Is it hard to get hired for a flexible data annotation analyst?

Getting hired as a flexible data annotation analyst generally depends on having basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, making the role accessible to a wide range of candidates. However, competition can vary based on the employer and location, and some roles may prefer candidates with prior experience or specific technical knowledge.

What are the most commonly searched types of Data Annotation Analyst jobs in Arizona?

The most popular types of Data Annotation Analyst jobs in Arizona are:

What are popular job titles related to Flexible Data Annotation Analyst jobs in Arizona?

For Flexible Data Annotation Analyst jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Flexible Data Annotation Analyst jobs in Arizona look for?

The top searched job categories for Flexible Data Annotation Analyst jobs in Arizona are:

What cities in Arizona are hiring for Flexible Data Annotation Analyst jobs?

Cities in Arizona with the most Flexible Data Annotation Analyst job openings:

Flexible Data Annotation Analyst jobs near you
Infographic showing various Flexible Data Annotation Analyst job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, and 3% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

AI Data Scientist Expert - Remote

YO AI Labs

Phoenix, AZ • Remote

$100 - $200/hr

Part-time

Posted 9 days ago

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.