Responsibilities

• Data Cleaning: Extract, clean, and organize datasets from multiple marketing platforms (e.g., Google Analytics 4, CRM platforms, and ad networks).
• SSOT Development: Design and implement end-to-end data pipelines for collecting, cleaning, and transforming data from disparate sources into our ecosystem.
• Architecture Management: Maintain and optimize scalable data warehouses and database structures (BigQuery) for client needs.
• Develop and maintain automated, client-facing dashboards and visual reports using tools like Looker Studio, Tableau, PowerBI or custom Python/R frameworks.
• Translate highly technical statistical findings into clear, executive-ready narratives and actionable recommendations for non-technical clients.
• Develop and implement statistical and machine learning models (e.g., attribution modeling, marketing mix modeling, churn prediction, and customer lifetime value).
• Conduct advanced predictive modeling to forecast campaign performance and optimize budget allocation across paid search, social, and programmatic media.
• Evaluate complex A/B testing and conversion rate optimization (CRO) efforts to ensure statistical validity and measure business impact.
• Work closely with SEO Strategists, Paid Media Managers, and Content Creators to identify algorithmic cross-channel opportunities.
• Stay ahead of industry trends, algorithm updates, and emerging AI technologies to continuously improve internal agency reporting and data capabilities.

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field
• 2–4+ years of experience in a data analytics or data science role, ideally with exposure to a digital marketing or agency environment
• Proficiency in SQL and Python
• Experience building automated dashboards in Looker Studio, Tableau, or Power BI
• Soft Skills: Exceptional written and verbal communication skills, with the ability to "tell a story" using data to executives and clients