Executive Director, Field Decision Intel

Bayer•Tulsa, OK

6d•$220,240 - $330,360•Onsite

About The Position

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 leader will build and oversee a modern analytics capability that combines advanced analytics, AI agents, decision-support frameworks, and field co-creation to improve customer engagement outcomes. Rather than operating a traditional centralized insights function, this role will define how AI analytics are framed, governed, validated, and operationalized by field leaders and customer-facing teams. As a trusted advisor to Customer Engagement leadership, this individual will establish the frameworks, knowledge assets, quality standards, and analytical approaches needed to ensure field teams can effectively leverage AI-generated insights, coaching, recommendations, and decision support. The role serves as a bridge between the field, analytics, data science, and digital organizations—ensuring AI-driven capabilities translate into measurable business impact, behavioral change, and improved customer outcomes. 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.

Requirements

Minimum of a Bachelor's degree
High leadership experience in commercial analytics, decision intelligence, data science, AI-enabled analytics, or related functions
Pharmaceutical, biotech, healthcare, or life sciences experience
Demonstrated experience applying AI, advanced analytics, machine learning, or agentic systems to commercial decision making, customer engagement, or business transformation
Experience leading AI-enabled analytics teams, products, or strategic transformation initiatives
Deep understanding of customer engagement, commercial execution, and business analytics
Demonstrated success leading large, cross-functional teams
Strong executive communication and influencing skills
Proven ability to drive organizational change and transformation

Nice To Haves

Advanced degree (MBA, MS, PhD)
12+ years of leadership experience in commercial analytics, decision intelligence, data science, AI-enabled analytics, or related functions
Experience developing governance, QA/QC, and evaluation frameworks for AI systems and agents
Experience building knowledge management and prompting frameworks for enterprise AI adoption
Experience with predictive analytics, field intelligence, and customer engagement technologies
Strong track record of linking analytics-driven initiatives to measurable business outcomes

Responsibilities

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 Segmentation teams to evaluate the effectiveness of targeting approaches, customer engagement strategies, and resource deployment through advanced analytics and AI-supported decision intelligence.
Partner closely with Customer Engagement Leadership, Field Operations & Field Effectiveness, Targeting & Segmentation, Marketing, Medical Affairs, Market Access, Learning & Development, Digital Product Teams, Data Science & AI, Knowledge Management, and Finance.
Ensure alignment of resources, priorities, and initiatives to maximize customer and business impact.
Recruit, develop, and retain a high-performing team of AI-fluent analysts, decision scientists, and analytics consultants.
Foster a culture of accountability, innovation, customer focus, and continuous improvement.
Establish clear performance expectations and development pathways.
Build organizational capabilities that support the evolving needs of an AI-enabled commercial organization.