ED, Head of Analytics Engineering

Role Summary

This role is for ED, Head of Analytics Engineering, located in East Hanover, NJ. The Insights and Decision Science (IDS) team aims to enable improved decision-making by leveraging data and advanced analytics to generate actionable insights that drive business growth. The leader will architect systems, standards, and capabilities to enable high-quality, scalable analytics across the organization and institutionalize analytics engineering as a core discipline.

Responsibilities

• Establish and champion analytics rigor, including statistical standards, validation protocols, and QA practices.
• Define enterprise-wide frameworks for measurement, performance metrics, and reporting standards.
• Enable cross-functional synergy by connecting analytics efforts across Commercial, Medical, Market Access, and other domains.
• Institutionalize analytics engineering as a core discipline, including reusability of data pipelines, analytics automation, and production-grade analytics solutions.
• Develop scalable capabilities that allow solutions to be transferred across use cases quickly and effectively.
• Support governance and compliance, ensuring analytical outputs meet regulatory and ethical standards.

Qualifications

• Required: Bachelor's or master‚Äôs degree in business administration, Computer Science, Engineering, or a related field.
• Required: 10+ years of experience in data/analytics, with demonstrated success in building scalable systems or frameworks.
• Required: Proven track record of establishing analytics standards, governance, or platform capabilities.
• Required: Strong cross-functional experience, ideally within Commercial, Medical, or Market Access analytics in life sciences or a regulated industry.
• Required: Experience with analytics engineering, BI tooling, and data infrastructure concepts.
• Required: Excellent communication and influence skills, especially with technical and non-technical stakeholders.

Skills

• Systems thinking with an enterprise view of how analytics drive decisions.
• Builder mindset with ability to create structure from ambiguity and scale impact.
• Balance between strategic design and operational execution.
• Deep understanding of the data lifecycle from ingestion to decision-making impact.

Education

• Bachelor's or master's degree in related field as listed in Qualifications.