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

Job Title

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

Location: Spring House, Pennsylvania, United States; alternative location: Titusville, New Jersey, United States.

Role Overview

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.

We are seeking a dynamic leader to help drive the data science and data engineering strategy for our OCMO 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.

We also use patient safety signals to partner with our PSTS organization to better understand their possible causes 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.

Key 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.

Qualifications

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

Preferred Skills

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

Benefits

Subject to the terms of their respective policies and date of hire, employees are eligible for the following time‑off benefits:

• Vacation – 120 hours per calendar year.
• Sick time – 40 hours per calendar year; Colorado 48 hours, Washington 56 hours.
• 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.

For additional general information on Company benefits, please visit https://www.careers.jnj.com/employee-benefits.

Pay Transparency

Anticipated base pay range: $164,000.00 – $282,900.00.

Employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)). This position is eligible to participate in the Company’s long‑term incentive program.

EEO Statement

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.

Accommodation Statement

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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Tagged as: Data Analysis, Data Visualization, Python, SQL