Associate Director, AI and Data Scientist

Overview

Job Summary The Associate Director, AI and Data Scientist is a hands-on experienced technical leader who specializes in applying AI and data science in the context of Pharma R&D operational processes towards AI transformation. This may involve leading or contributing to AI projects that leverage diverse data and information to augment and accelerate current workflows. The role will focus on developing data science, AI solutions, use-cases, and applications as well as efficiently conducting research on feasibility of such solutions.

While keenly focusing on business utility, and how AI transforms processes, the role will go deep into providing architectural and design guidance on the use of AI and data science, new processes and workflows to cross-functional teams and at times leading the implementing state-of-the-art AI solutions for business processes within R&D and across Corporate Functions.

Job Summary The AI and Data Scientist will develop leading-edge technical solutions such as multi-agent orchestration, pragmatic uses of generative AI, and robust reusable AI and data science solution capabilities as part of cross-functional teams including life sciences subject matter experts and technical development teams, including AI engineers and AI platform engineers. The role will continue to stay current with evolving technologies, gaining experience in new technology to guide better implementation of projects and providing guidance to cross-functional teams where needed.

The AI and Data Scientist will work with other Data Science, AI Scientists, AI engineers, and others within the larger Data Science and AI team in designing, developing, and implementing robust solutions for Otsuka. The role will partner with cross-functional teams such as IT and other stakeholders to ensure that efficient and effective solutions are developed and ultimately lead to AI transformation.

Job Description

• AI product strategy:
  Develop a product vision and roadmap specifically for AI-driven solutions, aligning AI capabilities with business objectives, technology, and market trends. Implement Data Science and AI portfolio objectives and contribute to the development of data and analyses strategies esp. in augmenting and accelerating R&D Operations while leveraging AI
• AI and ML Models:
  Experiment with, develop and train or fine-tune high quality effective AI models for business problems and processes, validate and evaluate them for fielding as part of broader solutions. Demonstrate strong foundational understanding of AI/ML, statistics, and data science concepts.
• Generative AI:
  Expertise in generative AI, including concepts like prompt engineering, embeddings, and fine-tuning, is often required for building and upgrading modern AI solutions. Core understanding of evaluation of LLMs quantitatively and qualitatively. Hands-on experience demonstrated in developing and fielding enterprise fieldable AI systems. Investigate and conduct PoC initiatives and develop solutions for new AI applications using advanced technologies like LLMs and Gen-AI to enhance data analytics capabilities to advance and effectively accelerate candidates across drug development phases.
• Data-driven decision making:
  Use data analysis and KPIs to monitor product performance and make informed decisions, considering evaluation metrics for AI models in delivering business value, esp. in Pharma R&D operations and Enterprise use cases.
• Understanding of Pharma R&D Data:
  Possess a deep and expansive understanding of data in drug development, clinical trials, external healthcare data to build AI solutions that conform to responsible AI, privacy by design, and regulatory compliance.
• User centric solution design and development:
  Deliver effective AI enabled products that build trust, drive adoption, and lead to transformation. Ensure a design-centric approach through deep understanding of user needs, processes, regulations, and responsible AI.
• Guide AI ecosystem capabilities:
  Provide technical input on AI ecosystem, AI platform, AI frameworks and architecture including AI solution evolution, and new capability development. Guide developers and other technical team members as well as direct vendors to provide oversight on AI concepts and their implementation. Remain current with industry trends and advancements in AI/ML, R&D processes and data, providing insights to help team leadership influence the organization's technical roadmap and strategy.
  
  Identify and apply innovative analytical solutions with a focus on adopting novel AI tools, methodologies, and technologies, including Gen AI and AI/ML applied to internal and external data
• Agentic AI frameworks and architecture:
  Design, implement and deploy agentic AI systems utilizing perception, planning, reasoning, orchestration, execution, and reflection loops. Demonstrate deep experience in architecting and deploying AI agent-based solutions.
• Understanding MLOps and LLMOps:
  Possess strong knowledge of processes and tools for…