Marketing Analytics Manager - AI Model Training - Remote

Job Type: Contractor

Location: Remote

Role Description

If you’re a senior marketing analytics professional who thrives on measurement rigor, attribution nuance, experimentation, and data-driven growth strategy, this is a unique opportunity to contribute directly to how the next generation of AI systems reason about marketing performance. You’ll challenge and evaluate advanced language models on domain-specific topics such as multi-touch attribution, paid media performance, cohort analysis, and conversion rate optimization to strengthen model reasoning and improve how AI systems communicate marketing insights.

Your Profile

• 4 years of professional experience in marketing analytics, growth analytics, marketing science, revenue analytics, or a closely related field.
• Significant hands-on work with marketing performance data, including paid media, web analytics, CRM, lifecycle marketing, campaign reporting, experimentation, or customer funnel analysis.
• Deep knowledge of attribution modeling, CAC/LTV analysis, funnel optimization, customer segmentation, marketing KPIs, and performance measurement frameworks.
• Strong understanding of statistical reasoning, A/B testing, incrementality, cohort analysis, data visualization, and the limitations of common marketing measurement approaches.
• Proven experience translating complex marketing data into clear business recommendations for executives, marketing leaders, product teams, or growth stakeholders.
• Bachelor’s degree in marketing, business analytics, statistics, economics, data science, mathematics, or a related field; a master’s degree or MBA is preferred.
  
  

Key Responsibilities

• Evaluate AI-generated responses for accuracy, clarity, analytical rigor, and practical usefulness in marketing analytics contexts.
• Challenge advanced language models with complex marketing analytics scenarios, including attribution tradeoffs, funnel diagnostics, campaign performance analysis, and growth forecasting.
• Review and refine AI-generated prompts, model responses, reasoning chains, and explanations related to marketing data, metrics, and decision-making.
• Identify errors, omissions, misleading assumptions, or weak analytical logic in AI-generated marketing recommendations.
• Provide structured feedback that helps improve model behavior, domain accuracy, and the quality of AI-supported marketing analysis.
• Shape AI communication standards for how models explain dashboards, statistical findings, experiment results, campaign outcomes, and business implications.
• Support benchmarking efforts by creating and evaluating tasks that test model performance across real-world marketing analytics use cases.
• Contribute domain expertise to improve how AI systems handle executive summaries, performance narratives, and actionable marketing recommendations.