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Remote Data Annotation Analyst Jobs in Texas (NOW HIRING)

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... quality assurance, and data annotation and labeling. What We Offer * Flexible schedule

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... quality assurance, and data annotation and labeling. What We Offer * Flexible schedule

... depth data analysis. Using analytic discovery and evaluation, our Customer Experience Analysts ... Call Annotation: Perform detailed annotations to understand customer intents, evaluate AI ...

... annotation guidelines and ensuring label quality. * Evaluate and apply the appropriate approach for ... Perform structured analysis of system performance to surface failure modes, data gaps, and high ...

The Data Analyst helps RightNow Media turn data into trusted, consistent, and actionable insight ... Schedule Full-time, Monday through Friday Work Location Fully remote **Please note we will not ...

We are looking for a Data Analyst to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude and creativity ...

ABOUT THE POSITION As Truvani's Junior eCommerce Data Analyst, you will leverage analytics ... Remote Work and Education Stipend * Truvani Monthly Store Credit * Position is available ...

ABOUT THE POSITION As Truvani's Junior eCommerce Data Analyst, you will leverage analytics ... Remote Work and Education Stipend * Truvani Monthly Store Credit * Position is available ...

ABOUT THE POSITION As Truvani's Junior eCommerce Data Analyst, you will leverage analytics ... Remote Work and Education Stipend * Truvani Monthly Store Credit * Position is available ...

ABOUT THE POSITION As Truvani's Junior eCommerce Data Analyst, you will leverage analytics ... Remote Work and Education Stipend * Truvani Monthly Store Credit * Position is available ...

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Remote Data Annotation Analyst information

How does a Remote Data Annotation Analyst typically collaborate with team members and ensure consistent labeling standards?

As a Remote Data Annotation Analyst, you’ll frequently work within a distributed team, using collaboration tools such as Slack, project management platforms, and shared annotation guidelines. Regular virtual meetings and feedback sessions help ensure everyone applies labeling standards consistently and resolves ambiguities. It’s common to review peer annotations and participate in quality assurance checks, promoting a culture of accuracy and continuous improvement. Clear communication and attention to detail are essential for maintaining high-quality annotated datasets across the team.

What are Remote Data Annotation Analysts?

Remote Data Annotation Analysts are professionals who label, categorize, or tag data—such as images, text, audio, or video—from a remote location. Their work helps train machine learning algorithms by providing structured datasets that computers can learn from. These analysts use specialized tools to identify relevant features in raw data, ensuring accuracy and consistency. The role often requires attention to detail, basic technical skills, and the ability to follow specific guidelines or instructions. This position is commonly found in industries like artificial intelligence, autonomous vehicles, and natural language processing.

What is the difference between Remote Data Annotation Analyst vs Remote Data Labeler?

AspectRemote Data Annotation AnalystRemote Data Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentHome-based, flexible hoursHome-based, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnalyzing and verifying labeled data, quality controlLabeling data, annotating images, text, or audio

The main difference is that Remote Data Annotation Analysts focus on verifying and ensuring the quality of labeled data, often involving analysis and review, while Remote Data Labelers primarily perform the task of labeling or annotating raw data. Both roles are essential in AI development and share similar work environments and skill requirements, but their specific responsibilities differ in scope and focus.

What are the key skills and qualifications needed to thrive as a Remote Data Annotation Analyst, and why are they important?

To thrive as a Remote Data Annotation Analyst, you need strong attention to detail, analytical thinking, and a high school diploma or equivalent, with many roles preferring experience in data-related tasks. Familiarity with data annotation platforms (like Labelbox or AWS SageMaker Ground Truth) and basic understanding of data management tools are typically required. Excellent time management, self-motivation, and clear communication help analysts manage remote workloads and collaborate effectively with distributed teams. These skills ensure accurate, high-quality annotated data essential for training and validating machine learning models.
What are the most commonly searched types of Data Annotation Analyst jobs in Texas? The most popular types of Data Annotation Analyst jobs in Texas are:
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What cities in Texas are hiring for Remote Data Annotation Analyst jobs? Cities in Texas with the most Remote Data Annotation Analyst job openings:

Philosophy QA Lead - Remote

YO IT Consulting

San Antonio, TX • Remote

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Description

Job Title: Philosophy Quality Assurance Lead

Job Type: Contract

Location: Remote

About This Role

In this hourly, remote contractor role, you will work as a Philosophy Quality Assurance Lead to oversee quality, consistency, and trainer performance across philosophy-focused AI training projects. You will review AI-generated philosophy content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for conceptual accuracy, argument structure, logical validity, philosophical context, interpretation quality, clarity, nuance, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong philosophy expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your philosophy quality leadership will directly help improve the world’s premier AI models by ensuring that philosophy training data is conceptually precise, logically sound, well-contextualized, nuanced, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Your Profile
  • Bachelor’s, Master’s, or PhD degree in Philosophy, Ethics, Logic, Political Theory, Humanities, Religious Studies, Classics, Cognitive Science, or a closely related field.
  • Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
  • 3+ years of experience in philosophy research, teaching, writing, editing, academic review, ethics review, logic instruction, or related humanities workflows.
  • Strong understanding of philosophical methods, logic, argument analysis, ethics, epistemology, metaphysics, philosophy of mind, political philosophy, history of philosophy, and conceptual clarification.
  • Ability to evaluate philosophy content against detailed rubrics and identify issues such as strawman arguments, invalid inference, conceptual confusion, oversimplification, unsupported claims, false equivalence, or misrepresentation of philosophers’ views.
  • Familiarity with areas such as formal logic, moral philosophy, applied ethics, analytic philosophy, continental philosophy, ancient philosophy, political philosophy, philosophy of science, or AI ethics is preferred.
  • Experience leading or supporting remote teams of researchers, writers, reviewers, educators, annotators, or QAs is strongly preferred.
  • Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
  • Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
  • Experience with AI training, data annotation, LLM evaluation, academic QA, ethics review, or rubric-based review is a strong plus.
Key Responsibilities
  • Quality monitoring: Spot-check philosophy items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
  • Philosophy review: Evaluate AI-generated philosophy explanations, argument analyses, ethical reasoning, summaries of philosophers, logic problems, and conceptual comparisons for accuracy and rigor.
  • Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and philosophy-specific review standards.
  • Question handling: Respond to trainer/QA questions clearly and promptly, especially around argument validity, conceptual distinctions, philosophical traditions, interpretation, ethics, logic, and rubric interpretation.
  • Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
  • Documentation: Create and maintain philosophy project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
  • Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and philosophy-specific review requirements.
  • Quality alignment: Ensure all trainers and QAs apply philosophy-review guidelines consistently and understand updates as projects evolve.
  • Reasoning and ethics review: Flag invalid, misleading, biased, overconfident, poorly argued, or ethically shallow philosophical content.
  • Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for philosophy AI training projects.
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