Director, Safety Data Science

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more atjnj.com

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About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more athttps://www.jnj.com/innovative-medicine

The Safety Analytics team within Global Medical Safety (GMS) is seeking aDirector, Safety Data Science to lead the development and deployment of advanced analytics, artificial intelligence, machine learning, and data science capabilities that improve medical safety decision-making, operational effectiveness, and business outcomes.

The Director is responsible for:

• Developing and implementing analytical, AI, and machine learning solutions that support Global Medical Safety objectives.
• Leading projects and project teams to deliver scalable analytical products, platforms, and decision-support capabilities.
• Establishing fit-for-purpose data assets, pipelines, models, dashboards, and applications that enable data-driven decision making.
• Provide scientific and technical leadership across the full spectrum of safety and operational analytics capabilities, including predictive safety analytics, quality monitoring and risk assessment

The Director is an influential leader with a strong understanding of Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, and Medical Safety. As a key member of the GMS Safety Analytics team, he/she will:

• Shape the direction of Safety Analytics, AI, Machine Learning, and Data Science within Global Medical Safety.
• Deliver projects with high levels of scientific rigor, operational excellence, quality, and measurable business value.
• Establish and execute strategy for Safety Analytics and AI capabilities.
• Promote innovation and adoption of emerging analytical technologies.
• Influence senior stakeholders and support strategic decision-making.
• Build organizational capabilities through recruitment, mentoring, development, and retention of analytics talent.
• Drive adoption of analytical and AI-enabled solutions through effective stakeholder engagement and change management.

Responsibilities

Advanced Analytics & AI

• Develop, validate, deploy, and optimize statistical, machine learning, deep learning, natural language processing, and generative AI solutions supporting medical safety and business objectives.
• Apply advanced analytical methods to quality monitoring, operational analytics, risk monitoring, translational analytics, and strategic decision-making.
• Evaluate and implement emerging technologies and methodologies that improve organizational capabilities.

Data Science & Solution Development

• Define requirements for scalable data pipelines, analytical data assets, and reusable analytics products.
• Work with healthcare, safety, real-world, and other enterprise data sources to generate actionable insights.
• Lead development of analytical capabilities that improve efficiency, decision-making, and patient safety outcomes.
• Partner with Information Technology and Digital organizations on collaborative initiatives.

Visualization & Decision Support

• Develop dashboards, visualizations, and analytical applications that communicate insights and support business decisions.
• Stakeholder Engagement & Scientific Leadership
• Provide technical expertise and analytical leadership to cross-functional stakeholders.
• Communicate insights, recommendations, and strategic opportunities to leadership teams.
• Contribute to scientific publications, industry collaborations, conferences, and external engagements.

Leadership

• Lead strategic initiatives with increasing organizational complexity and impact.
• Mentor and develop analytics professionals while fostering a culture of innovation, collaboration, and continuous learning.
• Drive organizational adoption of new analytical capabilities and best practices.

Qualifications

Advanced degree (PhD preferred; Master's degree with significant relevant experience considered) in Statistics, Biostatistics, Data Science, Computer Science, Mathematics, Bioinformatics, Biomedical Informatics, Epidemiology, or a related quantitative discipline.

Significant experience leading advanced analytics, machine learning, artificial intelligence, data science, healthcare analytics, medical safety analytics, or related scientific functions.

Experience supporting medical safety, pharmacovigilance, real-world evidence, healthcare analytics, or related life-science functions is required.

Demonstrated ability to:

• Lead analytics, AI/ML, or quantitative scientific initiatives.
• Build end-to-end analytical solutions from data acquisition through deployment and business adoption.
• Translate analytical concepts into scalable, production-grade solutions delivering measurable business value.
• Lead projects, teams, and cross-functional initiatives.

Experience working with healthcare, safety, real-world, or enterprise-scale data environments is preferred.

Experience presenting scientific work to technical and non-technical audiences is required.

Skills

• Proficiency in Python, R, and SQL.
• Expertise in statistical methods, predictive modeling, machine learning, deep learning, generative AI, and large language models.
• Understanding of cloud-based analytical architectures
• Experience deploying AI/ML solutions using modern MLOps, CI/CD, and model lifecycle management practices.
• Understanding of data engineering, feature engineering, and scalable analytical architectures.
• Understanding of regulatory expectations, validation principles, governance requirements, and responsible AI practices.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Ability to bridge business strategy, scientific methodology, and technical implementation to deliver organizational impact.

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.  

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
 

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