Tech Stack

Description

You will lead the development of advanced analytics frameworks to drive marketing performance and strategic growth, owning full-funnel insights, attribution models, and optimization strategies. Your work will directly shape marketing decisions and investment priorities across channels.

Requirements

• Bachelor’s degree in Marketing, Business, Statistics, Data Science, or a related field
• 6+ years of experience in marketing analytics or data science with proven track record of driving measurable impact
• Expert-level proficiency in SQL and either Python or R for data manipulation and statistical analysis
• Strong understanding of statistical modeling, marketing attribution, and predictive analytics
• Experience with data visualization tools (e.g., Tableau, Power BI) and web analytics platforms (e.g., Google Analytics)
• Experience with CRM and marketing automation platforms (e.g., Salesforce, Marketo)
• Ability to synthesize complex data into clear, actionable insights for both technical and non-technical stakeholders
• Excellent communication, collaboration, and project management skills

Responsibilities

• Serve as a strategic partner to marketing leadership, translating business goals into data-driven strategies and measurable outcomes.
• Architect and advocate for a unified customer data model, collaborating with data engineering to ensure scalable, high-quality data infrastructure.
• Lead the development of attribution models and marketing mix analyses to identify high-impact campaigns and optimize spend.
• Build and maintain executive-level dashboards and operational reporting tools to monitor marketing performance across channels.
• Conduct deep-dive analyses of customer behavior, campaign effectiveness, and channel ROI to uncover growth opportunities.
• Define and track key metrics such as Customer Acquisition Cost (CAC), Lifetime Value (LTV), and conversion rates.
• Design and analyze A/B tests to improve campaign performance and user experience.
• Partner with marketing operations to enhance automation, segmentation, and targeting strategies using data insights.
• Improve data accuracy, reporting processes, and analytics workflows across the marketing organization.
• Analyze digital performance across SEO/SEM, website traffic, social media, and email campaigns.
• Collaborate cross-functionally with Finance, Sales, and Product to align marketing analytics with broader business objectives.