Marketing Analytics Manager

The Marketing Analytics Manager, Marketing Operations, will lead the development of scalable measurement, reporting, and insights capabilities that strengthen marketing performance and support firm growth objectives. This role is responsible for establishing a unified marketing KPI framework, managing recurring reporting cadences, developing executive-level dashboards, and delivering actionable insights that inform strategic decisions across Marketing, Sales, Finance, and senior leadership. The ideal candidate combines analytical rigor, business acumen, and strong stakeholder partnership to improve performance visibility, enhance operational discipline, and enable data-driven planning across marketing initiatives, spend, and project portfolios.

What You'll Do:

• Provide day-to-day direction for offshore analytics resources supporting performance measurement, digital analytics, data visualization, segmentation, predictive modeling, and marketing insights.
• Lead end-to-end analytical projects, including test design, data collection and preparation, modeling, visualization, interpretation, and communication of findings.
• Translate complex data into actionable recommendations that improve acquisition, retention, channel mix, marketing ROI, LTV/CAC, NPS, and overall marketing performance.
• Develop and maintain standardized weekly, monthly, and quarterly reports, executive dashboards, and Q  materials covering lead generation, digital engagement, channel performance, earned impressions, risks, opportunities, and key marketing metrics.
• Build forecasting models, predictive analytics, and actionable segmentation to support marketing and sales planning, targeted communications, journey analysis, prioritization, and strategy.
• Establish and maintain data governance practices that improve accuracy, consistency, documentation, reliability, and stakeholder confidence across marketing and sales data.
• Partner with Marketing, Sales, Finance, and cross-functional stakeholders to define requirements, align on a unified KPI framework, and deliver analytics solutions tied to business priorities.
• Evaluate analytics tools, processes, and resources to identify opportunities for automation, efficiency, scalability, and adoption of emerging analytics capabilities and best practices.
• Develop data-informed perspectives on industry trends, competitor activity, brand health, and reputational risk using media, social, brand, and performance data.

What You Need to Have:

• Bachelor’s degree in Marketing, Business, Analytics, Statistics, Economics, Finance, Computer Science, or a related field; an equivalent combination of education and experience may be considered.
• Seven or more years of experience in marketing analytics, business analytics, data insights, performance measurement, or a related analytical function.
• Experience developing KPI frameworks, dashboards, reporting cadences, and executive-ready insights that support business decision-making.
• Demonstrated experience with advanced analytics, data visualization, and reporting tools, including Excel and PowerPoint; experience with SQL, Power BI, Tableau, or similar tools preferred.
• Experience partnering with cross-functional teams to translate business objectives into measurable reporting, analysis, and recommendations.
• Advanced proficiency with analytics, reporting, and visualization tools, including Excel and one or more platforms such as SQL, Power BI, Tableau, Python, R, or similar tools.
• Strong understanding of marketing performance measurement, KPI frameworks, campaign analytics, attribution, channel performance, ROI, LTV/CAC, funnel metrics, and executive reporting cadences.
• Ability to translate complex data into clear, concise, executive-ready insights, dashboards, business review materials, and recommendations for audiences with varying technical backgrounds.
• Working knowledge of CRM, marketing automation, web analytics, and Mar Tech platforms such as Salesforce, Marketo, Google Analytics, or related systems.
• Working knowledge of statistics, experimental design, A/B testing, regression analysis, segmentation, and predictive modeling.
• Ability to establish and maintain data governance…