Executive Director, Field Decision Intel

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ‘Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us.

If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Purpose:

The Executive Director, Field Decision Intelligence is a strategic leader responsible for advancing AI‑enabled analytics, decision intelligence, and customer engagement effectiveness across the Customer Engagement organization.

This role will be based in Whippany, NJ. Candidates not commutable to the Whippany, NJ site must be willing/able to relocate as a remote working arrangement will not be accommodated. Relocation assistance may be offered based on the needs of the business.

• Lead the vision, strategy, and evolution of AI-enabled customer engagement analytics and decision intelligence capabilities across the Customer Engagement organization;
• Establish the strategic framework for how AI-generated analytics, recommendations, and coaching insights are governed, interpreted, and operationalized within Customer Engagement;
• Serve as a senior thought partner to Customer Engagement leadership on how AI and analytics should shape field decision making;
• Translate enterprise and brand objectives into AI-enabled analytical approaches that drive measurable business outcomes;
• Lead field analytics for one of our priority brands, serving as player/coach to reshape capabilities and way of working of the field analytics team.

• Serve as the senior leader accountable for ensuring AI‑enabled insights, recommendations, and agentic capabilities are trusted, actionable, and scalable;
• Establish governance, QA/QC processes, monitoring frameworks, and corrective action mechanisms to continuously evaluate and improve the performance of AI analytics agents;
• Define standards for insight quality, recommendation relevance, explainability, consistency, and business value across AI‑enabled analytics solutions;
• Identify emerging AI capabilities and evolve analytics operating models to support increasingly autonomous forms of decision support.

• Build and maintain a curated knowledge base of critical business questions, analytical methodologies, decision frameworks, prompting approaches, and best practices to improve field adoption of AI‑enabled analytics;
• Develop repeatable frameworks that translate AI‑generated outputs into actionable field guidance and measurable business outcomes;
• Codify how business questions should be asked, framed, and answered to consistently drive field action;
• Establish standards for how insights are structured, delivered, and consumed by field leaders.

• Partner directly with field leaders to co‑create analytical approaches, decision‑support models, and coaching strategies;
• Enable Customer Engagement leaders to leverage AI‑enabled analytics, coaching recommendations, and decision‑support capabilities to improve customer engagement effectiveness;
• Drive best‑practice sharing and scaling of successful AI‑enabled decision approaches across teams and brands;
• Establish structured review processes with Customer Engagement leadership and field stakeholders to assess insight quality, adoption, behavioral change, business outcomes, and AI effectiveness.

• Serve as player/coach on the team responsible for delivering customer engagement analytics, opportunity identification, performance measurement, predictive analytics, and AI‑driven recommendations;
• Deliver proactive insights that enable leadership and field teams to make better decisions faster;
• Partner with Field Operations, Targeting, and…