Senior Director, AI & Data Science Solutions
Otsuka · Princeton, Mercer County ·
- Seniority
- Senior
- Category
- Data science
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
- Provide technical and engineering support for Data and Information Governance, quality, and FAIR data
Team and Organizational Leadership
- Build, mentor, and lead a high-performing and collaborative team of data scientists, AI/ML scientists, life cycle support.
- Foster a culture of innovation, continuous learning, accountability, cohesiveness, and respect, within and across teams, and stakeholders.
- Effectively manage the team, budget, resource allocation, and project timelines for the data and AI Solutions portfolio.
Oversight and Governance
- Ensure that all data and AI initiatives and applications adhere to internal governance standards, data privacy regulations (e.g., GxP, HIPAA), and responsible AI principles.
- Collaborate with Legal and Compliance teams to embed auditability and traceability into AI and Gen AI workflows.
- Serve as AI and Data Solutions expert for internal portfolio as well as organization wide initiatives, reviews, and AI committees.
- Establish and manage robust monitoring, alerting, and incident response processes for all AI capabilities and solutions within the remit.
- Effectively manage and provide oversight on vendors and vendor resources providing support to data and AI engineering portfolio
- Lead or participate in meetings related to Data or AI, its impact, enablement, governance, determining or enabling roadmaps and strategy as needed.
Cross-functional Collaboration
- Work closely with Data and AI Platform team and leverage platform level capabilities, solutions provided by IT as well as share data and AI solution needs as well as guidance with respective providers (Data and AI platform, IT infrastructure, etc.)
- Build strong, trusted relationships with key stakeholders across R&D, Scientific and Operations AI Data Science teams, other DnA pillars, IT, and external partners.
- Partner with R&D teams to translate complex scientific challenges into clear, executable data and AI projects.
- Communicate strategy, progress, and outcomes to diverse stakeholders, including technical teams and executive leadership.
- Lead as subject matter expert, while communicating, and collaborating effectively to ensure portfolio success.
Qualifications/ Required
Knowledge/ Experience and Skills:
- 12+ years of progressive leadership experience in data science, AI/ML, and Gen AI with at least 5 years in senior technical leadership or management roles with strong team management and development.
- Strong and demonstrated experience in architecting, building and maintaining large-scale data and AI solutions in a scientific, regulated, or research-heavy environment.
- Strong experience working within the pharmaceutical, biotech, or life sciences industry, particularly within R&D, is highly desirable along with a deep understanding of AI and Machine Learning and its applications in Pharma.
- Proven track record of implementing and deploying Gen AI and large language model (LLM) applications in production environments.
- Creative problem solving using responsible use of technology.
- Expertise in real-world data assets and using them to generate scientific evidence and guide operational effectiveness and efficiencies.
- Deep expertise across data science, representation, Gen AI, AI and machine learning techniques and experience in architecting and delivering AI/ML use cases.
- Strong team leadership, internal and cross-functional collaboration, project management skills with a focus on delivering impactful initiatives.
Educational Qualifications
- Masters in Mathematical, Engineering, or Scientific disciplines such as Computer Science, Mathematics, Engineering, Physics, Statistics, or a related field with focus on advanced and modern Data Science, including the use of AI and machine learning. PhD is strongly preferred.
Competencies
Accountability for Results - Stay focused on key strategic objectives, be accountable for high standards of performance, and take an active role in leading change.
Strategic Thinking & Problem Solving - Make decisions considering the long-term impact to customers, patients, employees, and the business.
Patient & Customer Centricity - Maintain an ongoing focus on the needs of our customers and/or key stakeholders.
Impactful Communication - Communicate with logic, clarity, and respect. Influence at all levels to achieve the best results for Otsuka.
Respectful Collaboration - Seek and value others’ perspectives and strive for diverse partnerships to enhance work toward common goals.
Empowered Development - Play an active role in professional development as a business imperative.
Application Deadline: This will be posted for a minimum of 5 business days.
Company benefits: Comprehensive medical, dental, vision, prescription drug coverage, company provided basic life, accidental death & dismemberment, short-term and long-term disability insurance, tuition reimbursement, student loan assistance, a generous 401(k) match, flexible time off, paid holidays, and paid leave programs as well as other company provided benefits.
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Disclaimer:
This job description is intended to describe the general nature and level of the work being performed by the people assigned to this position. It is not intended to include every job duty and responsibility specific to the position. Otsuka reserves the right to amend and change responsibilities to meet business and organizational needs as necessary.
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