Director, R&D Data Science & Digital Health – OCMO (Office of the Chief Medical Officer)

Johnson & Johnson Innovative Medicine•Ambler, PA

18h•Onsite

About The Position

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. Johnson & Johnson Innovative Medicine is recruiting for a Director, R&D Data Science & Digital Health – OCMO (Office of the Chief Medical Officer). This position has a primary location of Spring House, PA but is also open to Titusville, NJ. 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. We are seeking a dynamic leader to help drive the data science and data engineering strategy for our OCMO (Office of the Chief Medical Officer) organization. The OCMO Data Science team applies advanced analytics and data engineering to forecast potential patient safety signals using our scientific understanding of disease biology across patient cohorts, and to interpret incoming adverse event (AE) signals in partnership with safety organizations. The team also uses patient safety signals we receive (AE's) to partner with our PSTS organization to better understand their possible cause, and feed those insights back to our Discovery organization for the design of our next generation of molecules. This role will lead a team to build end-to-end capabilities that connect biology-informed hypotheses to scaled analytics—spanning AI-ready data engineering, predictive modeling, and insight-to-Discovery translation. A central expectation of this role is to ensure the organization has robust, future-proof data pipelines, governed data products, and traceable data foundations that enable safety signal forecasting and rapid signal interpretation at scale.

Requirements

Advanced degree (MS or PhD) in Data Science, Biostatistics, Computational Biology, Biomedical Engineering, or related field.
Significant experience leading end-to-end Data & AI solutions in biomedical/life sciences contexts, including stakeholder leadership and delivery in a matrixed environment.
Demonstrated experience designing and delivering scalable data pipelines, data models/repositories, and AI-ready data products; ability to translate business needs into engineering requirements.
Experience implementing data quality standards, lineage/versioning, and documentation that enable traceability and reproducibility.
Proficiency with modern data engineering and analytics tooling (Python/R/SQL, cloud services, workflow orchestration, version control).

Nice To Haves

Advanced Analytics
Budget Management
Compliance Management
Critical Thinking
Data Analysis
Data Privacy Standards
Data Quality
Data Reporting
Data Savvy
Data Science
Data Visualization
Developing Others
Digital Fluency
Inclusive Leadership
Leadership
Program Management
Strategic Thinking
Succession Planning

Responsibilities

Lead development and deployment of analytics & AI approaches to support safety signal detection and translational interpretation.
Apply model governance, versioning, and validation practices aligned with R&D AI expectations.
Build analytic workflows to ingest, triage, and interpret AE/safety signals with safety partners, generating actionable hypotheses.
Design, develop, and maintain scalable data pipelines to acquire, integrate, and manage relevant R&D/safety data from diverse sources.
Transform raw inputs into standardized, analysis-ready, AI-ready datasets for modeling and decision support.
Build and evolve data repositories and data models; optimize data flows for structured and unstructured data.
Implement data quality and performance standards, KPIs, and monitoring to ensure accuracy and consistency.
Establish data versioning and lineage to support traceability, compliance, and documentation of data architectures/workflows.
Partner with data engineering and ontology/knowledge-graph teams to advance harmonized scientific data models and interoperability.
Translate safety insights into clear feedback for Discovery to inform next-generation molecule design (closed-loop learning).
Define priorities and align stakeholders on a roadmap; communicate progress and recommendations to senior leadership.
Build, mentor, and lead a high-performing Data Science team for this new and exciting area.

Benefits

Company’s consolidated retirement plan (pension)
Savings plan (401(k))
Long-term incentive program
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
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