Remote Environmental Social Science Jobs (NOW HIRING)

Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking an Anthropology Quality Assurance Lead to oversee quality and consistency across anthropology-focused AI training projects, ensuring that all content adheres to expected quality standards and is culturally sensitive and ethically aware.
Responsibilities:
• Quality monitoring: Spot-check anthropology items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Anthropology review: Evaluate AI-generated anthropology explanations, ethnographic summaries, cultural comparisons, archaeology discussions, human evolution explanations, and social/cultural reasoning for accuracy and sensitivity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and anthropology-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around cultural context, anthropological concepts, ethnographic methods, archaeology, human evolution, ethics, representation, 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 anthropology 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 anthropology-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply anthropology review guidelines consistently and understand updates as projects evolve.
• Bias and ethics review: Flag ethnocentric, stereotyping, culturally insensitive, outdated, unsupported, or ethically problematic anthropology content.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for anthropology AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Anthropology, Cultural Anthropology, Archaeology, Biological Anthropology, Linguistic Anthropology, Sociology, Area Studies, Museum Studies, 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 anthropology research, teaching, ethnography, archaeology, museum/heritage work, cultural analysis, academic writing, fieldwork, or related workflows.
• Strong understanding of anthropological theory, cultural relativism, ethnographic methods, kinship, ritual, language/culture relationships, material culture, human evolution, archaeology, ethics, and representation.
• Ability to evaluate anthropology content against detailed rubrics and identify issues such as cultural stereotyping, ethnocentrism, unsupported generalizations, outdated terminology, methodological errors, weak contextualization, or ethically problematic framing.
• 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.
Preferred:
• Familiarity with areas such as ethnography, participant observation, archaeological methods, human origins, kinship systems, religion/ritual, migration, colonialism, Indigenous studies, museum ethics, or linguistic anthropology.
• Experience leading or supporting remote teams of researchers, educators, reviewers, fieldworkers, annotators, or QAs.
• Experience with AI training, data annotation, LLM evaluation, social science QA, academic review, cultural sensitivity review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.