Data Labeling Analyst V

Summary:
We're looking for experienced social media marketing practitioners to serve as domain experts evaluating AI-powered business tools covering performance analytics, brand listening, and creator partnerships on Facebook and Instagram.

You'll judge whether AI outputs are accurate, insightful, and genuinely useful to a business across performance diagnostics, brand sentiment monitoring, and creator partnership recommendations. This is a systematic evaluation role—you'll apply structured QA methodologies to assess AI quality at scale, not just offer subjective opinions.

What You'll Do
Rate and score AI-generated outputs across multiple quality dimensions using defined rubrics
Cross-verify data accuracy against ground truth (metrics, audience breakdowns, sentiment labels)
Identify patterns of failure—where the AI hallucinates, gives generic advice, or misreads data
Participate in calibration sessions to maintain inter-rater consistency
Contribute to evaluation methodology design and rubric iteration
Surface quality patterns to inform model improvements and quality benchmarks
Collaborate closely with Program Managers, data analysts, and data labelers

Required Qualifications
3+ years in social media marketing, digital marketing, or performance marketing (agency, in-house, or freelance) with hands-on experience in two or more of the following:
Performance analytics & diagnostics: Interpreted content metrics (reach, engagement rate, completion rate, saves, shares, follower growth), diagnosed why content performed well or poorly, identified patterns across formats/timing/topics, and made data-informed strategy recommendations
Brand monitoring / social listening: Tracked brand mentions, classified sentiment (positive/negative/neutral, including sarcasm and ambiguity), managed reputation spikes, identified themes driving conversation, and recommended response strategies. Familiarity with tools like Brandwatch, Sprout Social, Meltwater, or native platform analytics
Influencer/creator marketing: Sourced and vetted creators, evaluated audience demographics (age/gender/location breakdowns), assessed brand-creator fit, identified red flags (fake engagement, competitive conflicts, brand safety), and written or reviewed brand-to-creator outreach
Deep familiarity with Facebook and Instagram business ecosystems—you understand algorithmic distribution, engagement dynamics, content formats, and audience behavior differences across platforms
Ability to distinguish genuinely insightful analysis from surface-level number recitation—you know what a good strategist would say vs. what a dashboard already shows
Understanding of creator tier dynamics (nano through macro) and how partnership evaluation differs by scale
AI/LLM familiarity: Comfort working with AI-generated outputs and understanding where large language models commonly fail (hallucination, confident incorrectness, generic responses, data fabrication)

Preferred Qualifications
Quality assurance / systematic evaluation experience: Prior work in QA, content quality assurance, annotation/labeling, or AI output evaluation. Experience designing rubrics, executing test cases against edge cases, maintaining inter-rater reliability, or working in structured evaluation pipelines (RLHF, red-teaming, data labeling)
Experience in content moderation, trust & safety, or policy enforcement at scale
Background in data annotation, labeling pipelines, or RLHF workflows
Familiarity with evaluation frameworks (precision/recall thinking, confusion matrices, gold-standard labeling)
Experience across multiple verticals or business types
Multilingual capabilities for evaluating non-English AI outputs

What You'll Evaluate
Are cited metrics, percentages, trends, and audience breakdowns factually accurate?
Is sentiment classification correct, including edge cases (sarcasm, mixed, non-English)?
Are performance diagnoses genuinely non-obvious (root causes, correlations) or just restating numbers?
Are strategic recommendations specific, proportionate, and evidence-backed—not generic advice?
Are creator recommendations genuinely good fits (vertical, audience, content style, brand safety)?
Are competitive conflicts, authenticity red flags, or brand safety issues correctly identified?
Are outreach messages personalized to specific creators, or templated?

This posting is for a contract assignment with Tundra Technical Solutions to provide services to Meta

The pay range that Tundra in good faith reasonably expects to pay for this position is $19.85/hour - $24.81/hour.

Tundra’s benefits offering includes optional medical, dental, vision, retirement benefits, up to 15 Days PTO per annum and a New Child Benefit.

We would like to thank you for your interest in this opportunity. However, only candidates under consideration will be contacted.

Tundra Technical Solutions is a global workforce and technology delivery firm, ranked by Staffing Industry Analysts as one of the largest in North America. At Tundra, we aren't just hiring top talent at the world's most recognizable brands; we are pioneers of social recruitment.

This post is for a contract assignment. Assignment duties and duration are subject to business needs and requirements. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other legally protected characteristics.

California Notice: Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation

Meta and Tundra Technical Solutions, its recruiting services provider, use software with artificial intelligence and automated processing features to assist with recruiting for this role, including sourcing and reviewing applications. A recruiter or hiring manager decides which candidates advance.

The Meta CWX Program is enabled by a cutting-edge software platform called TalentNet that leads the contingent labor world for technology innovation. The software platform leverages Machine Learning and Artificial Intelligence to make sure the right people end up in the right job.

At Meta, we are constantly iterating, solving problems, and working together to connect people all over the world. That’s why it’s important that our workforce reflects the diversity of the people we serve. Hiring people with different backgrounds and points of view helps us make better decisions, build better products, and create better experiences for everyone.

We give people the power to build community and bring the world closer together. Our products empower more than 3 billion people around the world to share ideas, offer support, and make a difference