Director, R&D Neuroscience Data, Data Science & Artificial Intelligence - Ophthalmology

Director, R&D Neuroscience Data, Data Science & Artificial Intelligence – Ophthalmology

Johnson & Johnson Innovative Medicine is recruiting for Director, R&D Neuroscience Data, Data Science & Artificial Intelligence – Ophthalmology to be located at one of our sites in Cambridge, MA, Titusville, NJ, Spring House PA, or La Jolla, CA. Remote work arrangements may be considered on a case-by-case basis and if approved by the company.

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.

Role Summary

We are seeking a visionary Director, R&D Neuroscience Data, Data Science & Artificial Intelligence – Ophthalmology to join the Neuroscience Data, Data Science & Artificial Intelligence (DDSAI) team. This leader will shape and execute innovative strategies leveraging multimodal data sources, digital health technologies, computer vision, artificial intelligence (AI), and clinical/real-world evidence (RWE) to accelerate drug discovery and development, and maximize patient impact. By combining ophthalmology expertise with strong data science acumen, this role will enhance clinical trial execution and ensure that new solutions are patient-centric and ready for regulatory and payer acceptance. As an integral member of a highly matrixed team, the Director will collaborate with cross-functional experts in the Neuroscience Therapeutic Area, Clinical Development, Quantitative Sciences, Regulatory Affairs, and Patient-Reported Outcomes, and forge strategic external partnerships to infuse new ideas and capabilities. This is a unique opportunity to redefine how we understand and treat eye diseases—uncovering novel digital biomarkers and endpoints, stratifying patients for more personalized care, and ultimately delivering better outcomes for people living with ophthalmic diseases.

Key Responsibilities

• Innovative Data Analysis: Drive the development and application of advanced AI/ML methods, including cutting-edge computer vision techniques applied to ophthalmic imaging data (e.g., Optical Coherence Tomography and fundus images), to uncover disease mechanisms and identify novel biomarkers.
• Digital Endpoints & Tools: Lead the development and validation of novel digital endpoints. Engage with regulatory stakeholders to ensure these innovations enhance clinical trial design, improve patient monitoring and care pathways, and meet regulatory requirements.
• Advanced Statistical Modeling: Develop and apply sophisticated statistical models using real-world and clinical data to generate insights into disease progression, treatment outcomes, and patient stratification. Leverage longitudinal disease modeling, Bayesian methodologies, and causal inference techniques to inform decision-making.
• Generative AI & Multimodal Integration: Apply emerging generative AI approaches to boost data analysis and knowledge discovery, integrating diverse multimodal datasets (imaging, clinical, wearable, etc.) for a more holistic understanding of ophthalmic diseases.
• Real-World Evidence Integration: Partner with Clinical Development and Medical Affairs to integrate RWE into evidence generation strategies. Support trial optimization and regulatory submissions by incorporating insights from large-scale clinical datasets, electronic health records (EHRs), and other real-world data sources.
• Collaboration & Leadership: Build strong cross-functional collaborations within the company and spearhead external partnerships with academic institutions, technology providers, regulators, and industry consortia.

Qualifications

• An advanced degree (PhD, MD, or equivalent) in computational ophthalmology, neuroscience or a quantitative field such as biomedical engineering, data science, biostatistics, computational biology, or related discipline.
• 8+ years of relevant industry or academic experience with a strong record of success in applying data science within biology/medicine, ideally influencing cross-disciplinary teams at the intersection of data science, biomedical research, and clinical development.
• Experience in clinical development is required with experience in ophthalmology preferred.
• Deep experience in computer vision and deep learning applied to biomedical imaging (especially ophthalmic imaging such as fundus photography and OCT). Familiarity with model validation, reproducibility, and regulatory considerations for AI tools in healthcare.
• Experience working with large-scale, multimodal clinical datasets (including EHRs and sensor/wearable data). Proven skills in advanced statistical modeling (e.g., longitudinal analyses, Bayesian methods, causal inference) to glean meaningful insights from complex data.
• Hands-on experience implementing digital health technologies—such as wearables, sensors, and mobile platforms—in clinical research or care settings. Understanding of how to operationalize these tools in clinical trials is a plus.
• Proficiency in programming and data analysis tools/environments (e.g., Python, R, or comparable platforms) with a hands-on ability to develop and validate analytical workflows.
• Excellent communication skills with the ability to translate complex data-driven insights into clear, actionable strategies for diverse stakeholders, including senior leadership, clinicians, and external partners.
• A track record of scientific contributions demonstrated by relevant publications, conference presentations, or patents in fields such as data science, ophthalmology, or digital health.
• Familiarity with healthcare data standards, data privacy regulations, and the pathways for regulatory qualification of novel digital endpoints or AI tools.