Associate Director, AI Clinical Scientist

Job Summary

The Associate Director, AI Clinical Scientist in the Data Science and AI team will play a pivotal role in leading strategic and technical development and use AI solutions across scientific domains in Otsuka R&D. This is a technical role that requires proficiency in both traditional and generative AI and leveraging those methodologies to advance and accelerate drug development and evidence generation. The role will work closely with stakeholders and cross-functional teams to support Data Science and AI objectives in alignment with Otsuka's goals.

The ideal candidate will be an expert in AI and contribute to initiatives that enable novel evidence generation through expertise in biomarkers, including omics and digital health technologies (DHT), as well as clinical and real-world data (RWD). Additionally, the candidate will have strong skills in computational data analysis, artificial intelligence, and mathematical modeling, with an emphasis on applying machine learning and AI methodologies.

The Associate Director may also assist in overseeing a team of data or AI scientists, managing resources, providing trainings, advising cross-functional teams on the uses, limitations, and impact of AI and ML, and collaborating with internal and external partners to deliver high-quality data and analytic products.

Job Description

• Implement Data Science and AI portfolio objectives and contribute to the development of data and analyses strategies across all phases of drug development, from Discovery and Preclinical to Clinical stages while extensively leveraging AI
• Identify and apply innovative analytical solutions with a strong focus on adopting novel AI tools, methodologies, and technologies, including machine learning, tokenization, and digital health technologies (DHTs)
• Development and application of novel advanced analyses for biological data, including digital, sensor data, metabolomics, proteomics and genomics to support new drug development and decision making
• Investigate and conduct Proof of Concept (PoC) initiatives, and develop solutions for new AI applications using advanced technologies like Large Language Models (LLMs) and Generative AI (Gen-AI) to enhance data analytics capabilities
• Assess the feasibility and potential impact of integrating Gen AI, LLMs, and other small AI models into existing workflows, and recommend adoption strategies based on PoC outcomes
• Work with cross-functional teams to support deep scientific data analyses, leverage AI and gen AI capabilities effectively for Otsuka's drug development portfolio and evidence generation efforts throughout the drug lifecycle
• Leverage Gen AI and AI/ML applications across the organization, emphasizing their transformative potential in drug development processes
• Develop processes to optimize data and analytics systems and their execution, ensuring alignment with cutting-edge technological advancements
• Guide the scientific and technical evaluation, selection, and planning of analysis for transitional and digital biomarkers, along with the data generated in clinical trials
• Lead the planning, development, and implementation of data science solutions that leverage novel AI methodologies
• Guide team members on AI and other methodologies and foster a culture of innovation and collaborative success
• Collaborate with internal and external stakeholders to identify opportunities for innovation and experimentation with emerging technologies in data science and analytics
• Serve as a subject matter expert, ensuring effective awareness, communication, and collaboration to achieve portfolio success
• Remain current with industry trends and advancements in AI/ML, providing insights to influence the organization's technical roadmap and strategy
• Build a strong presence both internally and externally through publications in relevant and reputable conferences and journals

Qualifications / Required Knowledge / Experience and Skills

• 5+ years of experience in AI and advanced data sciences within the pharmaceutical or Bio-Tech R&D industries
• Expertise in scientific data analyses in drug development and real-world data assets and using them to explore biomarkers, endpoints, and scientific or value evidence
• Proficiency in AI, Gen AI, and machine learning techniques and relevant tools (e.g., pytorch, TensorFlow, LLMs and related technologies)
• Expertise in digital health technologies and their applications in pharmaceutical research
• Strong project management skills with a focus on delivering impactful initiatives

Competencies

• Accountability for Results
• Strategic Thinking & Problem Solving
• Patient & Customer Centricity
• Impactful Communication
• Respectful Collaboration
• Empowered Development