Director, R&D Data Science & Digital Health, Real-World Evidence (RWE), Neuroscience

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 at jnj.com

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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, New Brunswick, New Jersey, United States of America, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

Johnson & Johnson Innovative Medicine is recruiting for Director, R&D Data Science & Digital Health, Real-World Evidence (RWE), Neuroscience

The primary location for this position is flexible – Titusville, NJ; Raritan, NJ; Spring House, PA; Cambridge, MA; or San Diego, CA.

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, immunology, neuroscience, cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine visit https://innovativemedicine.jnj.com/

The R&D Data Science & Digital Health, Real-World Evidence (RWE) team at J&J Innovative Medicine is dedicated to developing innovative evidence solutions and critical insights through diverse data sources including RWD, trial data and emerging innovative data sources to support clinical programs and regulatory submissions.

Role Summary:

We are seeking a highly skilled and motivated scientific director to join our RWE team. The successful candidate will apply advanced statistical methods to support algorithm development, patient stratification, innovative trial design and novel endpoint development for neuroscience. This role will help shape the next generation of data-driven solutions for neuroscience drug discovery and development, working closely with the Neuroscience Therapeutic Area, Clinical Development, Quantitative Sciences, Regulatory and Patient Reported Outcomes.

Key Responsibilities:

• Design, develop, and validate statistical approaches and algorithms for patient stratification, leveraging both clinical trial and real-world datasets.

• Lead the statistical design, analysis, and validation of novel digital endpoints (e.g., wearables, speech, cognition) for neuroscience.

• Partner with our multidisciplinary team to ensure biological and clinical relevance of patient stratification strategies and novel endpoints.

• Apply rigorous statistical methodologies to algorithm development, ensuring reproducibility, robustness, and regulatory readiness.

• Develop and maintain statistical analysis plans, simulation studies, and innovative methodologies tailored to multimodal datasets.

• Apply advanced statistical and machine learning methods to large-scale datasets, including EHRs, claims, registries and longitudinal cohort studies.

• End-to-end expertise in RWE research including conceptualizing research questions, data feasibility, study design, analysis, programming, and interpretation.

• Communicate findings and methodologies clearly to scientific, clinical, and non-technical stakeholders.

• Contribute to regulatory submissions, publications, and presentations at internal and at scientific meetings.

• Stay current with emerging statistical methodologies, regulatory guidance, and best practices in RWE.

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