Marketing Intelligence Analyst
Wellington Steele & Associates, Inc., Atlanta, Georgia, United States, 30383
The Marketing Intelligence Analyst serves as a critical driver of the marketing strategy and execution, transforming marketing data into actionable insights and predictive models that inform smarter, faster go-to-market decisions. This individual will not only produce and interpret marketing reporting but also partner closely with marketing leaders to shape campaign strategy, forecast performance, and optimize future initiatives.
They will play a pivotal role in supporting the marketing team’s strategic roadmap, using AI and data-driven intelligence to scale campaigns, enhance personalization, improve targeting and messaging effectiveness, and deliver measurable business impact across the funnel.
Key Responsibilities
Design, develop, and maintain marketing-focused dashboards using Power BI to provide real-time insights across campaigns, audiences/personas, content, and communication channels.
Analyze historical and current marketing performance data to identify trends, opportunities, and key drivers related to campaign effectiveness, audience engagement, and conversion.
Develop and apply predictive models to forecast campaign outcomes, optimize channel mix, timing, budget/spend, targeting, and support data-informed marketing planning and prioritization.
Support AI-driven marketing planning and initiatives, including multi-product campaigns, persona enrichment, precision engagement, experimentation, and performance testing.
Translate complex datasets and predictive analytics into clear, actionable recommendations for marketing leadership and team members, enabling decisions around messaging, spend allocation, and campaign design.
Collaborate closely with marketing, IT, and data engineering teams to integrate internal and external data sources, ensuring a unified, accurate view of marketing performance and customer behavior.
Develop and enforce processes to ensure accuracy, completeness, and consistency of marketing and sales datasets used for campaign reporting and optimization.
Contribute to the company’s data governance framework by defining and maintaining marketing-specific KPIs, metrics, and business rules aligned to campaign and go-to-market objectives.
Evaluate and optimize marketing‑owned data systems (e.g., Salsify, HubSpot, and related platforms), ensuring data is structured and maintained in ways that support effective marketing execution, insights, and predictive modeling.
Assist in operationalizing AI across campaign planning, budgeting, media modeling, forecasting, and closed‑loop learning systems to continuously improve marketing performance.
Monitor and evaluate the effectiveness of AI‑powered marketing initiatives, iteratively refining models, assumptions, and dashboards to maximize business and marketing impact.
Stay current with emerging marketing analytics tools, predictive modeling techniques, and AI applications relevant to modern marketing and go-to‑market teams.
Basic Requirements
Bachelor’s degree in Business, Marketing, Data Analytics, Information Systems, or related field.
5+ years of experience in business intelligence, analytics, or data analysis, with hands‑on experience supporting marketing teams or reporting on marketing campaign performance.
Strong proficiency with Power BI, including report building, data modeling, and DAX.
Solid understanding of SQL for querying and transforming data.
Experience working with marketing data sources (campaign, channel, audience, or engagement data).
Experience with ETL processes and handling structured and unstructured datasets.
Ability to work with APIs and integrate external partner or platform data into internal systems.
Experience with predictive modeling or advanced analytics techniques applied to marketing or customer data.
Preferred Qualifications
Experience with cloud data platforms such as Azure, Databricks, or similar.
Proficiency in Python, R, or similar tools for predictive analytics, automation, and data modeling.
Familiarity with marketing platforms such as HubSpot, marketing automation, CRM, or product/content data systems.
Knowledge of data governance, security, and best practices for handling marketing and partner‑provided data.
Experience in cross‑functional roles bridging marketing strategy, analytics, and IT/data engineering teams.
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They will play a pivotal role in supporting the marketing team’s strategic roadmap, using AI and data-driven intelligence to scale campaigns, enhance personalization, improve targeting and messaging effectiveness, and deliver measurable business impact across the funnel.
Key Responsibilities
Design, develop, and maintain marketing-focused dashboards using Power BI to provide real-time insights across campaigns, audiences/personas, content, and communication channels.
Analyze historical and current marketing performance data to identify trends, opportunities, and key drivers related to campaign effectiveness, audience engagement, and conversion.
Develop and apply predictive models to forecast campaign outcomes, optimize channel mix, timing, budget/spend, targeting, and support data-informed marketing planning and prioritization.
Support AI-driven marketing planning and initiatives, including multi-product campaigns, persona enrichment, precision engagement, experimentation, and performance testing.
Translate complex datasets and predictive analytics into clear, actionable recommendations for marketing leadership and team members, enabling decisions around messaging, spend allocation, and campaign design.
Collaborate closely with marketing, IT, and data engineering teams to integrate internal and external data sources, ensuring a unified, accurate view of marketing performance and customer behavior.
Develop and enforce processes to ensure accuracy, completeness, and consistency of marketing and sales datasets used for campaign reporting and optimization.
Contribute to the company’s data governance framework by defining and maintaining marketing-specific KPIs, metrics, and business rules aligned to campaign and go-to-market objectives.
Evaluate and optimize marketing‑owned data systems (e.g., Salsify, HubSpot, and related platforms), ensuring data is structured and maintained in ways that support effective marketing execution, insights, and predictive modeling.
Assist in operationalizing AI across campaign planning, budgeting, media modeling, forecasting, and closed‑loop learning systems to continuously improve marketing performance.
Monitor and evaluate the effectiveness of AI‑powered marketing initiatives, iteratively refining models, assumptions, and dashboards to maximize business and marketing impact.
Stay current with emerging marketing analytics tools, predictive modeling techniques, and AI applications relevant to modern marketing and go-to‑market teams.
Basic Requirements
Bachelor’s degree in Business, Marketing, Data Analytics, Information Systems, or related field.
5+ years of experience in business intelligence, analytics, or data analysis, with hands‑on experience supporting marketing teams or reporting on marketing campaign performance.
Strong proficiency with Power BI, including report building, data modeling, and DAX.
Solid understanding of SQL for querying and transforming data.
Experience working with marketing data sources (campaign, channel, audience, or engagement data).
Experience with ETL processes and handling structured and unstructured datasets.
Ability to work with APIs and integrate external partner or platform data into internal systems.
Experience with predictive modeling or advanced analytics techniques applied to marketing or customer data.
Preferred Qualifications
Experience with cloud data platforms such as Azure, Databricks, or similar.
Proficiency in Python, R, or similar tools for predictive analytics, automation, and data modeling.
Familiarity with marketing platforms such as HubSpot, marketing automation, CRM, or product/content data systems.
Knowledge of data governance, security, and best practices for handling marketing and partner‑provided data.
Experience in cross‑functional roles bridging marketing strategy, analytics, and IT/data engineering teams.
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