Senior Director, AI & Data Science Solutions

Job Summary

The Senior Director, AI and Data Science Solutions will be a visionary and strategic leader responsible for defining and executing the AI, Generative AI, and Data Science solutions strategy across the entire R&D value chain with a deep knowledge of AI, Generative AI and R&D Data, R&D workflows, clinical trial planning and execution. This role will empower scientific, as well as business functions—including drug development, clinical trials, real-world data evidence—by delivering or building robust, scalable, and compliant AI and data science solutions across drug development and implementing advanced data, AI and Generative AI (Gen AI) solutions.

As a senior technical leader, the Senior Director will manage a high-performing team of AI and data scientists, machine learning scientists and specialist developers to foster a culture of innovation, and ensure the adoption of best-in-class AI solutions practices within a regulated pharmaceutical environment. The leader will bridge the gap between scientific ambition and technical execution, translating complex R&D challenges into impactful data and AI solutions. The role will oversee a team, manage resources and overall operation and execution of portfolio while collaborate with DSAI and DnA leadership, internal and external partners to deliver high-quality data and analytic products.

The AI and Data Science Solutions team will focus on establishing and enhancing Otsuka’s Data and AI solutions foundations on top of the AI platform provided by Data and AI platform team in IT and working closely with AI and Data Engineering team in Data Science and AI function. This role will oversee team is a centralized capability and comprises of programmers, full-stack AI and data scientist who work closely with other Data and Analytics, AI engineers, Data Engineers, various roles in IT, and other business functions.

Job Description

Strategy and Vision

• Define and drive the strategic vision and roadmap for AI, Gen AI capabilities, solutions, use cases, and larger connected AI programs within R&D, aligning with overall business objectives and scientific priorities.
• Serve as a key thought leader and trusted advisor to senior R&D leadership on opportunities and risks related to AI and data technologies and Gen AI. Represent in key AI and Data solutions initiatives in Otsuka as needed.

• Deliver leading edge AI solutions approaches, effective enterprise AI and data strategy (specifically clinical, operational, and real-world data), robust and responsible AI/ML model development, fit-for-purpose clinical development data stewardship strategies to enable key data insights to inform decision making and assist in business transformation initiatives.
• Evaluate and adopt emerging data and AI technologies to create best-in-class scalable and robust AI solutions, balancing new opportunities with the need for scalability, reliability, and regulatory compliance.

 Execution and Technical Leadership

• Lead and deliver the design, development, and pre-deployment of extensible and scalable AI solutions for complex R&D Data, and solution architecture for AI applications to support all R&D data AI needs, including structured, unstructured (text, imaging, and data from sensors, medical devices, and digital apps), and real-time data.
• Lead quick feasibilities of AI solutions with DSAI portfolio as well as act as an advisor to the rest of the organization on AI solutions, pros and cons of approaches, various solution architecture choices, as needed.
• Oversee the implementation of AI and Gen AI use cases from ideation to production deployment, and application life cycle management working closely with AI and Data Engineering team. Hands on experience in architecting AI and Gen AI solutions, foundation for a diverse set of AI solutions.
• Lead and deliver data processing, representations, and AI solutions in R&D for applications ranging across: clinical trial optimization, patient recruitment, content authoring automation, asset management, pharmacovigilance, quality, regulatory, and enterprise functions, Real-World Data, sensor and medical device data, omics data.
• Champion feasibility and AI Solutions best practices, review AI solution architectures, and data & AI observability to ensure technical consistency, scalability, and effective governance of AI engineering across the portfolio of oversight.
• Architect and scale AI and ML practices for in house applications to support the entire model lifecycle—from experimentation and deployment to monitoring and retraining—while ensuring automation and reproducibility.
• Drive awareness of AI/ML applications and the importance of strong Data and AI engineering foundation across the organization
• Pr