VP, Data & Digital Quality

VP, Data & Digital Quality Job Function: Quality Job Sub Function: Digital Quality Job Category: People Leader Job Posting Locations: Horsham, Pennsylvania, United States of America; New Brunswick, New Jersey, United States of America Job Description The VP, Data & Digital Quality is accountable for architecting and executing the digital and data strategy that will reimagine Quality through advanced analytics, AI/ML, agentic orchestration, and next‑generation risk sensing capabilities. This leader accelerates the transformation from reactive compliance to predictive, intelligence‑driven Quality, leveraging enterprise data, automation, and digital products to improve risk visibility, strengthen decision‑making, and enhance patient safety. The role shapes the long‑term digital quality vision, drives the global roadmap, and ensures high‑quality delivery of platforms, predictive models, emerging technologies, and compliance systems across all regions and segments, and supports the Q&C digital talent development strategy. This leader partners with Regulatory, Technology, Business leaders and Quality colleagues to drive measurable improvements in quality outcomes and audit readiness by enabling the evolution of Quality practices to incorporate emerging technologies. Major Duties & Responsibilities Digital Product Strategy & Portfolio Delivery: Own and continuously evolve the enterprise portion of the Q&C Digital Strategy & Data 5‑Year Roadmap, including integration into long‑range financial planning, business planning and refresh cycles. Oversee and set high‑level strategy for sector Digital Strategy & Roadmap. Lead the strategic shift toward predictive digital quality, ensuring digital product roadmaps incorporate AI/ML, advanced analytics, data quality and adaptive risk models that proactively identify issues before they impact patients or compliance. Drive the integration of advanced technologies including automated and agentic risk alerts into Quality operations. Data Platforms, Architecture & Visualization: Build and scale an enterprise quality data architecture (structured and unstructured) that enables near‑real‑time data ingestion (where applicable), harmonization, AI‑ready data quality, and modeling to support rapid detection of trends, improves predictive and preventive capabilities, and accelerates Quality decision‑making. Advance capabilities in risk dashboards, anomaly detection, and quality signal intelligence using tools such as QUALIFI, ThoughtSpot, and modern cloud analytics stacks. Adoption of Emerging Technologies: Build and operationalize an AI/ML strategy for Quality, including use cases in process monitoring, automated document intelligence, complaint/risk signal extraction, audit prediction, and failure mode analytics. Scale GenAI and Agentic AI enabled quality workflows (e.g., intelligent QMS search, automated CAPA summarization, QA review assistance) while maintaining regulatory rigor and responsible AI guardrails. Oversee development of early‑warning systems that detect, contextualize, and elevate quality risks using multivariate models and cross‑value‑chain data signals. Champion responsible AI practices, ensuring models meet requirements for validation, transparency, explainability, and audit readiness. Evolve practices across Enterprise Quality to incorporate AI/ML model validation, continuous monitoring, and audit‑ready AI governance frameworks. Partners with Regulatory, Technology, and Legal to ensure digital innovation is aligned with emerging expectations for AI in regulated environments (FDA, EMA, global health authorities). Operational Excellence: Improve decision velocity by embedding AI‑enhanced insights into core quality operational processes, driving measurable improvements in cycle time, right‑first‑time, and risk reduction. Establish KPIs and OKRs that measure the value of digital products, data platforms, and predictive capabilities. Governance & Stakeholder Leadership: Serve as the enterprise leader for digital quality governance, ensuring alignment of data standards, AI/ML guardrails, and risk‑sensing capabilities across segments and regions. Co‑lead cross‑functional working groups with Supply Chain, R&D, Manufacturing, and Technology to embed digital quality intelligence into end‑to‑end operations. People Leadership & Culture: Build a high‑performing team of data scientists, digital product directors and managers, ML engineers, digital products owners, digital product analysts, quality technologists, and analytics translators. Foster a culture that embraces experimentation, iterative learning, and analytics‑driven decision‑making, while maintaining the highest standards of patient safety and compliance. Other Duties: Deep expertise in predictive analytics, machine learning, and AI/ML model lifecycle management in regulated environments. Experience building automated risk detection systems, predictive quality models, and advanced statistical monitoring tools. Demonstrated success modernizing Quality or Compliance functions through digital transformation, end‑to‑end data strategies, and AI‑enabled workflows. Strong understanding of pharma/medical device technology data governance, AI regulatory expectations, validation standards for ML systems, and GxP‑compliant cloud technologies. Proven ability to translate complex technical insights into business‑ready, risk‑focused decisions for senior leaders. Qualifications Required Minimum Education: Bachelor's Degree Years of Related Experience: 15+ years leading digital products and enterprise data/analytics in regulated industries. Years of People Management Experience: 8–10 years Knowledge, Skills and Abilities: Proven track record delivering digital strategies and measurable business value. Experience managing enterprise‑scale data platforms (QUALIFI/ThoughtSpot or equivalent). AI/ML and risk‑sensing product delivery experience. Strong governance, stakeholder engagement, and financial acumen. Global people leadership and a track record of people development. Required Skills Business Alignment Compliance Management Consistency Controls Compliance Developing Others Digital Assurance Emerging Technologies Fact‑Based Decision Making Inclusive Leadership Leadership Performance Measurement Product Strategies Quality Control (QC) Quality Standards Quality Validation Regulatory Compliance Tactical Planning Preferred Skills Business Alignment Compliance Management Consistency Controls Compliance Developing Others Digital Assurance Emerging Technologies Fact‑Based Decision Making Inclusive Leadership Leadership Performance Measurement Product Strategies Quality Control (QC) Quality Standards Quality Validation Regulatory Compliance Tactical Planning Percentage Traveled: up to 40% Compensation & Benefits The anticipated base pay range for this position is: $199,000.00 - $366,850.00 Benefits: Company‑consolidated retirement plan (pension) and savings plan (401(k)). Long‑term incentive program. Vacation – 120 hours per calendar year. Sick time – 40 hours per calendar year; 48 hours for Colorado, 56 hours for Washington. Holiday pay, including Floating Holidays – 13 days per calendar year. Work, Personal and Family Time – up to 40 hours per calendar year. Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child. Bereavement Leave – 240 hours for an immediate family member; 40 hours for an extended family member per calendar year. Caregiver Leave – 80 hours in a 52‑week rolling period. Volunteer Leave – 32 hours per calendar year. Military Spouse Time‑Off – 80 hours per calendar year. Equal Employment Opportunity Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. #J-18808-Ljbffr