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
    

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

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

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.

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

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.

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

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.

Guidelines

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