Director, Safety Data Science

Biopharma Careers; Horsham (PA); Hybride; USD 180 000 - 280 000; Plein temps

Résumé du poste

Johnson & Johnson, based in Horsham, PA, seeks a Director of Safety Data Science to lead advanced analytics and AI initiatives within Global Medical Safety. You will shape the strategy, deliver scalable data products, and mentor analytics professionals across the organization.

The role requires an advanced degree and深 expertise in ML/NLP, regulatory governance, and delivering measurable business value in medical safety analytics.

Qualifications

• PhD is preferred; Master's degree with significant relevant experience also considered.
• Experience leading analytics, AI/ML, or quantitative scientific initiatives.
• Experience with healthcare analytics or medical safety analytics is required.

Responsabilités

• Lead analytics, AI/ML, and data science initiatives across Global Medical Safety.
• Deliver scalable data products, dashboards, and decision-support tools.
• Mentor analytics professionals and drive adoption of new capabilities.
• Partner with IT and business stakeholders to translate insights into action.

Connaissances

Python

R

SQL

Statistical methods

Predictive modeling

Machine learning

Deep learning

Generative AI

Large language models

Cloud architectures

MLOps

Data engineering

Regulatory compliance

Stakeholder mgmt

Communication

Formation

PhD in Statistics/related field

Master's degree with relevant experience

Description du poste

## About this opportunityAt 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 at jnj.comAs guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.**Job Function:**Data Analytics & Computational Sciences**Job Sub Function:**Data Science**Job Category:**People Leader**All Job Posting Locations:**Horsham, Pennsylvania, United States of America, Titusville, New Jersey, United States of America**Job Description:****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 at https://www.jnj.com/innovative-medicineThe Safety Analytics team within Global Medical Safety (GMS) is seeking a **Director, 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 assessmentThe 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 & AIDevelop, 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 DevelopmentDefine 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 SupportDevelop dashboards, visualizations, and analytical applications that communicate insights and support business decisions.Stakeholder Engagement & Scientific LeadershipProvide 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.LeadershipLead 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 architecturesExperience 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.