Marketing Analytics Manager – AI Model Training | Remote

Marketing Analytics Manager AI Model TrainingWork Snapshot

• Job Type: Contract
• Location: Remote
• Compensation: Up to $100 per hour
• Level: Middle to Senior Level

Roles & Responsibilities

• Evaluate AI-generated marketing analytics content for analytical accuracy, attribution reasoning, statistical rigor, business relevance, and strategic usefulness
• Review AI-generated analyses, dashboards, reports, forecasts, and recommendations related to paid media performance, customer acquisition, lifecycle marketing, funnel optimization, retention analysis, and revenue growth strategies
• Challenge advanced AI systems with realistic marketing analytics scenarios involving attribution modeling, CAC/LTV analysis, cohort analysis, A/B testing, incrementality measurement, campaign optimization, and customer segmentation
• Analyze AI-generated reasoning related to multi-touch attribution, marketing mix modeling, conversion rate optimization, growth forecasting, customer journey analysis, and performance measurement frameworks
• Evaluate AI-generated recommendations across digital marketing channels including paid search, social advertising, email marketing, CRM campaigns, lifecycle programs, SEO, affiliate marketing, and performance marketing initiatives
• Identify analytical errors, weak assumptions, misleading interpretations, statistical flaws, unsupported conclusions, data inconsistencies, and unrealistic business recommendations in AI-generated marketing analyses
• Review and refine AI-generated prompts, responses, explanations, calculations, executive summaries, dashboards, and performance narratives to ensure alignment with accepted marketing analytics and growth strategy practices
• Assess whether AI outputs appropriately account for attribution limitations, measurement bias, sample size constraints, tracking gaps, incrementality challenges, and causal inference considerations
• Evaluate AI-generated reasoning involving customer funnels, acquisition channels, retention drivers, audience segmentation, campaign efficiency, conversion behavior, and marketing ROI optimization
• Interpret and assess marketing performance datasets, reporting frameworks, experimentation results, customer cohorts, attribution outputs, and analytics visualizations for accuracy and business applicability
• Compare and rank multiple AI-generated marketing analyses and recommendations based on clarity, statistical soundness, practical usefulness, business impact, and strategic reasoning quality
• Provide structured feedback documenting reasoning gaps, unsupported assumptions, attribution issues, flawed statistical logic, weak business interpretation, and unclear communication
• Create and review high-quality example responses demonstrating strong analytical thinking, statistically grounded reasoning, actionable business recommendations, and executive-ready communication
• Support benchmarking initiatives by designing, reviewing, validating, and calibrating marketing analytics tasks across varying levels of complexity and business contexts
• Help improve AI communication standards for marketing analytics topics by ensuring outputs present statistical findings, attribution insights, campaign results, and business implications clearly and responsibly
• Ensure AI-generated marketing recommendations reflect sound analytical methodology, realistic growth assumptions, defensible measurement practices, and practical business decision-making
• Support AI model improvement through annotation workflows, analytics evaluations, response ranking, quality assurance reviews, and structured documentation processes

Requirements

• Education: Bachelor s degree in Marketing, Business Analytics, Statistics, Economics, Data Science, Mathematics, or a related field required; Master s degree or MBA preferred
• Minimum Strong years of professional experience in marketing analytics, growth analytics, marketing science, revenue analytics, or a closely related analytical field
• Strong hands-on experience working with marketing performance data including paid media analytics, web analytics, CRM reporting, customer lifecycle analysis, experimentation, campaign measurement, and funnel optimization
• Deep understanding of attribution modeling, CAC/LTV analysis, customer segmentation, cohort analysis, funnel metrics, marketing KPIs, conversion optimization, and performance measurement methodologies
• Strong knowledge of statistical reasoning, A/B testing methodologies, incrementality analysis, causal inference concepts, and limitations of common marketing measurement frameworks
• Proven experience translating complex marketing data into actionable business recommendations for executives, marketing leaders, product teams, growth stakeholders, or revenue organizations
• Experience analyzing campaign performance across multiple acquisition and retention channels including paid search, social, CRM, lifecycle marketing, email, affiliate, and web analytics platforms strongly preferred
• Strong analytical thinking and attention to detail when evaluating marketing data quality, attribution logic, statistical validity, experimental design, and business interpretation
• Excellent written communication skills with the ability to explain complex analytical concepts, experiment findings, attribution tradeoffs, and performance insights clearly and concisely
• Ability to evaluate AI-generated marketing analyses for statistical accuracy, strategic reasoning, practical applicability, and executive communication quality
• Familiarity with marketing analytics workflows, dashboard interpretation, forecasting methods, customer journey analysis, and growth measurement frameworks preferred
• Previous experience with AI data training, analytics annotation, technical QA, or evaluation of AI-generated analytical content strongly preferred
• Familiarity with AI systems and tools such as ChatGPT, Gemini, Claude, Perplexity, or similar platforms preferred
• Reliable remote work practices, confidentiality handling, and consistency across structured analytics evaluation workflows required