About the job
We are seeking an experienced and visionary Senior Director to lead our data science and digital health strategy for ophthalmology. This role will shape and execute innovative approaches leveraging multiomics, digital health technologies, artificial intelligence, and clinical/real-world evidence (RWE) to accelerate drug discovery, development, and patient impact.
Responsibilities
Define and execute the data science and digital health strategy for ophthalmology, integrating computational biology, AI/ML, digital health, and clinical/RWE insights.
Drive the application of multiomics (genomics, proteomics, transcriptomics, metabolomics, etc.) and integrative analytics to uncover disease mechanisms, biomarkers, and novel targets.
Lead the development, validation, and regulatory engagement of digital tools and novel endpoints to enhance clinical trial design, patient monitoring, and care pathways.
Champion the use of machine learning, deep learning, gene
Qualifications
Minimum
Advanced degree (PhD, MD or equivalent) in neuroscience / quantitative sciences such as biomedical engineering, data science, biostatistics, computational biology or a related field is required.
10+ years of relevant industry or academic experience, with proven leadership in applying data-driven methods to drug discovery and development is required.
7+ years of experience as a people manager is required.
Excellent communication skills, with the ability to translate complex data-driven insights into clear strategies for senior stakeholders and external partners is required.
Technical Expertise in as least two of the three following areas is required: 1. Proficiency in multiomics integration (e.g., genomics, transcriptomics, proteomics,) and advanced statistical/causal inference methods; 2. Expertise in applying digital health technologies (wearables, sensors, mobile platforms) and novel endpoints in clinical research. 3. Experience with large-scale clinical datasets, EHR, and real-world data and expertise in advanced modeling, longitudinal analysis, and patient stratification.
Track record of scientific contributions (presentations and publications) in this field is required.
Familiarity with data standards, privacy regulations, and regulatory qualification pathways is required.
Competence with programming and analytics environments (e.g., Python, R) with ability to guide technical teams at a strategic level is required.
Demonstrated success in leading cross-disciplinary teams at the interface of data science, biology, and clinical development is required.
Preferred
Experience in clinical development with demonstrated expertise in ophthalmology preferred.
Knowledge of data infrastructures, development of data analysis pipelines and their implementation at scale, and state-of-the-art AI methodologies is a plus.