Marketing Data Analyst Job at Robert Half, Miami, FL

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  • Robert Half
  • Miami, FL

Job Description

Job Purpose:

The Marketing Data Analyst plays a vital role in driving data-informed decision-making by collecting, analyzing, and interpreting marketing data to optimize campaign performance, customer engagement, and return on investment. Supporting both strategic planning and execution, this role provides actionable insights to guide targeting, segmentation, and growth strategies across digital and traditional channels. By identifying trends, measuring performance, and benchmarking effectiveness, the analyst ensures marketing efforts are efficient, impactful, and aligned with business goals.

Key Responsibilities:

  • Data Collection & Management:
  • Integrate data from diverse sources including CRM systems, web analytics, social media, email platforms, and advertising tools. Ensure data integrity, consistency, and accuracy for effective analysis.
  • Data Analysis & Interpretation:
  • Analyze large datasets to uncover patterns, trends, and insights related to customer behavior, market dynamics, and campaign effectiveness, particularly within the insurance and financial services industries.
  • Reporting & Dashboards:
  • Design, develop, and maintain dashboards and recurring/ad hoc reports that visualize key performance indicators (KPIs) such as ROI, CPA, conversion rates, and customer lifetime value. Deliver insights clearly to marketing teams and stakeholders.
  • Customer Segmentation & Targeting:
  • Segment customers based on behavior and demographics to support tailored marketing strategies. Develop data-driven targeting frameworks to enhance personalization and campaign performance.
  • Campaign Performance & Optimization:
  • Evaluate marketing effectiveness across channels. Provide data-backed recommendations to improve outcomes and optimize resource allocation.
  • A/B Testing & Experimentation:
  • Design, implement, and analyze A/B tests and marketing experiments to enhance website performance, email engagement, and other marketing assets.
  • Predictive Modeling (Optional):
  • Develop models to forecast marketing outcomes, predict churn, and optimize lead scoring using statistical tools such as R or Python.
  • Data-Driven Strategy:
  • Translate analytical findings into actionable business recommendations that drive marketing strategy adjustments, audience engagement, and product alignment.
  • Marketing Technology Support:
  • Assist with the implementation and optimization of marketing and analytics platforms (e.g., CRM, automation tools). Ensure proper data tracking and integration.
  • Collaboration & Communication:
  • Partner with marketing managers, campaign specialists, and cross-functional teams to understand data needs. Communicate insights clearly to both technical and non-technical audiences.
  • Compliance & Privacy:
  • Ensure all data use and reporting activities comply with applicable data privacy laws and internal policies.

Qualifications:

  • Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Marketing, or related quantitative field.
  • 5+ years of experience in marketing data analysis, preferably in insurance or financial services.
  • Expertise in collecting, cleaning, analyzing, and interpreting data from multiple marketing platforms.
  • Proficiency in SQL and Excel (advanced); familiarity with R or Python (preferred).
  • Experience using data visualization tools (e.g., Tableau, Power BI, Looker Studio).
  • Deep understanding of KPIs and marketing metrics (e.g., ROI, CPA, LTV, conversion rates).
  • Experience with CRM systems (e.g., Salesforce, Dynamics 365) and marketing automation platforms (e.g., Marketo, HubSpot, Pardot).
  • Familiarity with web analytics tools (e.g., Google Analytics, Adobe Analytics).
  • Strong analytical thinking, attention to detail, and problem-solving skills.
  • Excellent verbal and written communication skills, with the ability to present complex data simply.
  • Demonstrated ability to work independently and in a team.
  • Strong grasp of data privacy and compliance practices.
  • Bilingual in Spanish and English (required).

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