Responsibilities

• Domain Training & Annotation
• Provide domain expertise during model training, ensuring AI systems understand marketing terminology, logic, and workflows.
• Label, curate, and validate datasets containing marketing materials (ad copy, campaign briefs, KPIs, customer segments, etc.).
• Design realistic scenarios and data prompts representing different marketing contexts (e.g., brand launches, A/B testing, multichannel campaigns).
• Workflow Simulation & Process Mapping
• Translate end-to-end marketing workflows (e.g., campaign planning execution measurement optimization) into structured training data for AI learning.
• Identify decision points, metrics, and dependencies in marketing operations that AI systems must recognize.
• Collaborate with ML engineers to represent these workflows in AI-friendly formats (taxonomies, knowledge graphs, or structured datasets).
• Model Evaluation & Feedback
• Review AI-generated outputs for marketing relevance, creativity, tone, and compliance.

Requirements

• Bachelor’s or Master’s degree in Marketing, Business, Communications, or related field.
• 7–12 years of hands-on experience in marketing, with exposure to:
• Campaign strategy and execution (digital, social, performance, and/or brand marketing)
• Marketing automation tools (HubSpot, Salesforce Marketing Cloud, Marketo, etc.)
• Analytics and measurement workflows (Google Analytics, Looker, Power BI, etc.)
• Customer segmentation, journey mapping, and content strategy
• Media planning, A/B testing, and ROI optimization
• Seo research using AI/ML methodology to get the best output.
• Proven ability to translate real-world marketing problems into structured data or process documentation.
• Excellent communication and documentation skills—able to articulate domain logic clearly to technical teams.