Otsuka Pharmaceutical Companies (U.S.) brings together pharmaceutical businesses focused on advancing healthcare through product commercialization and clinical development. Otsuka America Pharmaceutical, Inc. commercializes Otsuka-discovered and in-licensed medicines in North America, while Otsuka Pharmaceutical Development & Commercialization, Inc. leads clinical development and global registration of innovative healthcare products, with particular expertise in neuroscience. Together, these organizations operate across pharmaceuticals, healthcare, and biotechnology with a focus on developing solutions that support better health.
Associate Director, AI Solutions Scientist (US Remote)
Lead the architecture and delivery of generative AI, agentic systems, and machine learning products supporting pharmaceutical R&D and corporate functions. Guide cross-functional teams from feasibility research through production deployment.
Description
- Architect and build modern AI solutions, use cases, and applications
- Research the feasibility of proposed AI solutions
- Provide architecture and design direction across AI, data science, processes, and workflows
- Deliver advanced AI solutions for R&D and corporate functions
- Create multi-agent orchestration, generative AI applications, and reusable AI capabilities
- Track emerging AI technologies and direct their adoption across projects and teams
- Build robust AI solutions with data scientists, AI researchers, engineers, IT teams, and life sciences experts
- Define AI product visions and roadmaps aligned with business goals, technology, and market developments
- Apply data analysis and KPIs to track product performance and assess business value from AI models
- Develop solutions that support responsible AI, privacy by design, and regulatory compliance
- Experiment with, train, fine-tune, validate, and evaluate AI and machine learning models
- Design and deploy agentic AI systems incorporating perception, planning, reasoning, orchestration, execution, and reflection
- Oversee the production lifecycle and ongoing revisions of AI, ML, LLM, and agent systems
- Shape AI ecosystem capabilities, including platforms, frameworks, architecture, and new developments
- Mentor developers and oversee the application of AI concepts and implementation practices
- Lead or support AI/ML use-case reviews with subject-matter expertise and execution guidance
- Diagnose and resolve issues affecting data analytics and AI applications during development and production support
- Create and promote reusable data and AI components across business functions and the broader AI ecosystem
- Lead cross-functional groups of technical, semi-technical, and business stakeholders
- Keep stakeholders informed about AI progress, results, impact, limitations, risks, and expectations
- Translate complex AI concepts between technical teams and non-technical business partners
- Lead adoption and change-management initiatives for AI technologies
- Work with internal functions and external partners to build AI and machine learning capabilities
- Coordinate with data science, IT, cloud architecture, and platform teams to align solutions with enterprise architecture and compliance
- Partner with legal, privacy, and ethics teams on bias, fairness, transparency, and data privacy
- Work effectively through experimentation and iteration in AI product development
- Use intelligence and context to guide ongoing product evolution
Requirements
- Master’s degree in data science, computer engineering, computer science, physics, statistics, information systems, or a related discipline focused on advanced data science, AI, and machine learning
- PhD preferred
- Expertise in real-world data assets and using them to produce scientific evidence and improve operational effectiveness and efficiency
- Deep knowledge of data engineering, data representation, generative AI, artificial intelligence, and machine learning methods
- Experience designing and delivering AI and machine learning use cases
- Experience in software or product engineering
- Strong understanding of AI and machine learning applications in pharmaceuticals
- Experience with Dataiku Data Science Studio, AWS SageMaker, Snowflake, or comparable data science platforms
- Experience integrating machine learning and AI technologies with data engineering pipelines
- Strong knowledge of the software development life cycle and data science development lifecycle, including CRISP
- Experience engineering software or products based on AI and machine learning
- Familiarity with testing, validation, and GxP validation principles
- Experience building and maintaining large-scale data and AI solutions in scientific, regulated, or research-intensive environments
- Strong pharmaceutical, biotechnology, or life sciences experience, especially in drug development, clinical trials, or R&D, is highly desirable
- Record of implementing and deploying proof-of-concept and production generative AI, AI/ML, and large language model applications
- Understanding of life sciences R&D business processes
- Experience working with claims, clinical trial, regulatory, quality, and other life sciences operations data
- Understanding of data collection, governance, and structuring challenges that affect AI outcomes
- Strong collaboration, cross-functional teamwork, and project management abilities
- Excellent communication and stakeholder management skills
- Self-directed and effective working independently or collaboratively
- Creative problem-solving skills grounded in responsible AI and related technologies
Benefits
- Medical, dental, vision, and prescription drug coverage
- Company-paid basic life insurance
- Accidental death and dismemberment insurance
- Short- and long-term disability insurance
- Tuition reimbursement
- Student loan assistance
- Generous 401(k) matching
- Flexible time off
- Paid holidays
- Paid leave programs
- Additional company-provided benefits
- Incentive opportunity