Position Overview

The Senior Associate, Content Data Analyst is responsible for supporting global content strategy by delivering scalable analytics, standardized metrics, and actionable insights across the content ecosystem. This role operates at a global level, partnering with U.S. and international stakeholders to define, measure, and optimize content performance.

The analyst will drive reporting frameworks, develop global dashboards, and enable visibility into key content strategy metrics such as reuse, quality, cost efficiency, and adoption. This role requires a solid combination of analytics, stakeholder management, and strategic thinking.

Key Responsibilities

1. Global Content Metrics & Strategy Enablement
- Define and operationalize global content performance metrics (e.g., reuse, velocity, quality, cost, adoption).
- Translate business questions into scalable data models and reporting frameworks.
- Support strategic decision-making through data-driven insights and trend analysis.

2. Content Ecosystem Reporting




- Develop and maintain global dashboards that track the health of the content ecosystem.
- Standardize reporting across regions to ensure consistency and comparability of metrics.
- Identify trends, risks, and opportunities across content lifecycle and usage.

3. Advanced Analytics, Insights & Visualization
- Build advanced dashboards and analytical models using Power BI, SQL, and Python.
- Integrate data from AEM and other systems to provide unified reporting views.
- Generate insights that inform content strategy, optimization, and investment decisions.

4. Data Governance & Quality Management
- Establish and enforce data governance practices for content analytics and reporting.
- Define and document standardized metric definitions and reporting methodologies.
- Implement data quality monitoring frameworks to ensure accuracy and reliability.
- Drive continuous improvement in analytics capabilities and reporting maturity.

5. Global Stakeholder

📌 Sr. Associate (Hyderabad)
🏢 Amgen
📍 Hyderabad