Marketing Subject Matter Expert ( SME ) - Reopened

Marketing Subject Matter Expert (SME) – AI Model Training & Evaluation

Role Overview

We are seeking a Marketing Subject Matter Expert (SME) with strong domain expertise and analytical capabilities to support the training, evaluation, and fine-tuning of AI models for marketing applications. This role serves as the critical link between marketing strategy and AI systems, ensuring models accurately understand marketing concepts, workflows, decision-making processes, and business objectives.

The ideal candidate will bring extensive hands-on experience across the entire marketing funnel—from campaign strategy and content development to analytics, optimization, and customer engagement—along with a strong interest in leveraging AI to enhance marketing intelligence and automation.

You will collaborate closely with data scientists, machine learning engineers, and product teams to help build next-generation AI solutions, including marketing assistants, campaign optimization engines, audience intelligence systems, and predictive analytics tools.

Key Responsibilities

1. Domain Training & Annotation

• Provide marketing domain expertise during AI model training, ensuring systems accurately understand marketing terminology, logic, and workflows.

• Label, curate, validate, and refine datasets containing marketing-related content, including:

  • Ad copy
  • Campaign briefs
  • Customer personas
  • KPIs and performance metrics
  • Customer segments

• Design realistic marketing scenarios and prompts representing diverse business contexts, such as:

  • Brand launches
  • Performance marketing campaigns
  • A/B testing initiatives
  • Multichannel marketing programs

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2. Workflow Simulation & Process Mapping

• Translate end-to-end marketing workflows into structured training data for AI learning.

• Map campaign processes, including:

  • Campaign planning
  • Execution
  • Measurement
  • Optimization

• Identify key decision points, dependencies, and performance metrics that AI systems must understand.

• Partner with ML engineers to represent marketing workflows using AI-compatible structures such as:

  • Taxonomies
  • Knowledge graphs
  • Structured datasets

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3. Model Evaluation & Feedback

• Review AI-generated outputs for:

  • Marketing relevance
  • Creativity
  • Brand alignment
  • Tone and messaging consistency
  • Regulatory and compliance considerations

• Provide structured feedback and actionable recommendations to improve model performance and output quality.

• Develop and refine evaluation frameworks based on:

  • Campaign effectiveness
  • Audience targeting accuracy
  • Brand consistency
  • Content quality
  • Business impact

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4. Strategic Collaboration & Innovation

• Collaborate with product and engineering teams to define AI-driven marketing use cases, including:

  • Campaign recommendations
  • Content personalization
  • Audience segmentation
  • Performance forecasting
  • Marketing automation

• Identify opportunities where AI can improve marketing efficiency, productivity, and decision-making.

• Stay current with emerging marketing technologies, data platforms, and generative AI tools to inform model enhancement initiatives.

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Required Qualifications

• Bachelor's or Master's degree in Marketing, Business Administration, Communications, or a related field.
• 7–12 years of hands-on marketing experience, including exposure to:

Campaign Strategy & Execution

• Digital marketing
• Social media marketing
• Performance marketing
• Brand marketing

Marketing Technology & Automation

• HubSpot
• Salesforce Marketing Cloud
• Marketo
• Similar marketing automation platforms

Analytics & Measurement

• Google Analytics
• Looker
• Power BI
• Marketing performance reporting and dashboarding

Customer Experience & Content

• Customer segmentation
• Customer journey mapping
• Content strategy and planning

Optimization & Media Management

• Media planning
• A/B testing
• Conversion optimization
• ROI analysis and performance improvement

SEO & AI-Driven Research

• SEO strategy and keyword research
• Experience leveraging AI/ML methodologies and tools to improve SEO outcomes and content performance

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Additional Requirements

• Proven ability to convert real-world marketing challenges into structured data, workflows, or process documentation.

• Excellent written and verbal communication skills with the ability to clearly explain marketing concepts to technical teams.

• Experience collaborating cross-functionally with:

  • Data Science teams
  • Product teams
  • Engineering teams

• Strong analytical thinking and problem-solving abilities.

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Ideal Workflow Experience

Candidates should have practical experience managing or contributing to several of the following workflows:

1. Campaign Lifecycle Management

• Campaign brief creation
• Creative development
• Approval workflows
• Campaign launch and execution
• Performance tracking
• Post-campaign analysis and reporting

2. Performance Marketing

• Keyword research
• Bidding strategies
• Conversion tracking
• Landing page optimization
• A/B testing and experimentation

3. CRM & Marketing Automation

• Lead scoring
• Email nurturing and drip campaigns
• Audience segmentation
• Personalization strategies
• Customer retention programs

4. Content Strategy & Social Media

• Editorial calendar planning
• Content creation and optimization
• Influencer marketing campaigns
• Social media performance analysis
• Engagement measurement

5. Data-Driven Marketing

• Marketing analytics and reporting
• KPI tracking and interpretation
• Dashboard creation
• Campaign optimization using data insights

6. Brand & Communications

• Brand positioning
• Storytelling and messaging
• Tone of voice management
• Cross-channel communication consistency
• Brand governance and compliance

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Preferred Skills

• Experience working with Generative AI, Large Language Models (LLMs), or AI-assisted marketing platforms.
• Familiarity with data annotation, prompt engineering, or AI model evaluation methodologies.
• Understanding of customer data platforms (CDPs), marketing data ecosystems, and predictive analytics.
• Ability to bridge business requirements and technical implementation in AI-driven environments.