Director, AI Analytics and Reporting Enablement

Role Summary

Location: Philadelphia, PA, USA. The Director, AI Analytics & Reporting Enablement provides strategic leadership for enterprise analytics transformation within U.S. Commercial, owning the vision, strategy, and execution for scalable BI, GenAI, and advanced analytics capabilities. They enable data-driven decision-making across marketing, sales, market access, patient services, and enterprise teams, and set the long-term analytics enablement roadmap while ensuring governed, compliant data usage. The role combines hands-on BI/AI work with strategic leadership, mentoring a cross-functional team to drive innovation, operational excellence, and measurable business impact.

Responsibilities

• Strategy & Roadmap - Define and execute the multi-year strategy for enterprise BI, AI, and analytics enablement to maximize commercial impact.
• Commercial Use Case Prioritization - Identify, evaluate, and prioritize high-value analytics and AI use cases that advance brand, access, field, and omnichannel objectives.
• Platform Ownership - Serve as product owner for the AI enterprise analytics ecosystem, ensuring solutions are scalable, integrated, and user-centric.
• Governance & Compliance - Establish and maintain governance standards for data quality, semantic modeling, AI/ML lifecycle, and compliant analytics practices.
• Player-Coach Leadership - Lead, mentor, and develop the AI analytics enablement team while personally contributing hands-on to BI development and problem-solving.
• Stakeholder Partnership - Act as a strategic advisor to senior commercial leaders by translating analytics capabilities into clear business decisions and outcomes.
• AI/ML & GenAI Innovation - Drive evaluation, piloting, and scaling of advanced analytics, AI/ML, and GenAI solutions that enhance commercial performance.
• Operational Excellence - Oversee delivery of high-quality dashboards, reporting tools, and insight workflows that improve speed-to-decision and data reliability.
• Adoption & Change Management - Lead adoption efforts through training, storytelling, and change leadership to embed AI-first, data-driven ways of working.
• Vendor & Budget Oversight - Manage vendors, contracts, and analytics investments to ensure cost-efficient delivery of high-value capabilities.

Qualifications

• Required: Bachelor’s degree in quantitative or business discipline
• Required: At least 10 years of experience in analytics, data science, or business intelligence
• Required: At least 5 years of experience leading functional or cross-functional teams and driving cross-functional analytics initiatives
• Required: Experience scaling analytics platforms and driving broad enterprise adoption
• Required: Hands on experience with ThoughtSpot and Liveboards
• Required: Fluent in SQL, semantic modeling concepts, cloud data environments, and key commercial data sources (such as patient-level claims)
• Required: Proven track record of translating analytics into clear business impact as well as influencing senior stakeholders
• Required: Experience in balancing strategic leadership with hands-on technical contribution
• Preferred: MBA or advanced degree in Data Science, Statistics, Computer Science, or related field
• Preferred: 15+ years of experience in analytics, data science, or business intelligence
• Preferred: 8+ years of experience leading functional or cross-functional teams and driving analytics initiatives
• Preferred: Hands-on experience with BI/analytics tools (ThoughtSpot, Tableau, Power BI) including semantic data modeling
• Preferred: Familiarity with cloud environments (AWS, Azure, GCP) and data technologies (Spark, Databricks)
• Preferred: Proven track record leading, building and scaling advanced analytics, AI/ML, and GenAI solutions
• Preferred: Ability to simplify complex analytics into compelling, actionable business narratives
• Preferred: Proven track record influencing VP-level stakeholders and navigating complex cross-functional environments

Education

• Bachelor’s degree in quantitative or business discipline
• MBA or advanced degree in Data Science, Statistics, Computer Science, or related field