Director, Data Enablement and Reporting

About the role

The Director of Data Enablement and Reporting is a strategic leader in DnA and will define, execute, and oversee the data enablement and reporting analytics across the R&D organization. This role is responsible for the technical implementation of programs related to the use of data in various initiatives on data and support information governance policies.

Responsibilities

• Develop, champion, and execute the R&D data strategy roadmap, ensuring alignment with enterprise standards and regulatory requirements (e.g., GxP, HIPAA, GDPR).
• Design and operationalize a fit-for-purpose data governance framework, including policies, standards, data ownership models, and stewardship across R&D functions (e.g., Clinical Operations, Research, Regulatory, Safety).
• Oversee the implementation and maintenance of key data governance as well as data capabilities towards AI readiness, including metadata management, semantic annotations for internal and external data, data cataloging, and data lineage tracking.
• Establish data quality standards, define quality metrics (KPIs), and lead remediation initiatives to ensure high data integrity, completeness, and accuracy.
• Provide metrics on the readiness of data for its use in AI and Data Science solutions.
• Collaborate with stakeholders to understand their processes, AI needs, and convert them to prioritized AI portfolio in the domain of responsibility.
• Collaborate closely with Ethics and Compliance, Data Privacy, Information Security, IT and various R&D business functions to develop and deliver data strategy that is aligned to Otsuka priorities on leveraging and protecting data assets.
• Leverage deep understanding of variety of R&D data (Clinical trials, Textual data, Clinical data, safety, etc.) to develop pragmatic operational AI use cases; these may include analytics, traditional AI/ML, or Gen AI.
• Partner with R&D business owners and leadership to identify and deliver high-impact, governed data products and analytical reporting that support strategic insights and operational efficiency.
• Collaborate with Data Science and AI Engineering teams to build scalable data models, data lakes, and visualization tools that enable self-service analytics and advanced data applications.
• Establish and monitor service level agreements (SLAs) and usage metrics for data products and reporting dashboards, continuously improving their value and adoption.
• Communicate data governance priorities, reporting metrics, and value realization to executive leadership and business stakeholders.
• Act as a business liaison for AI and Data Science teams, translating functional R&D requirements into actionable data and governance initiatives in the areas of responsibility, such as clinical operations and management.
• Collaborate with AI/ML teams to ensure the data is trusted, compliant, and ready for use in advanced analytics and AI applications.
• Identify and evaluate opportunities to leverage AI technologies to automate reporting analytics and governance workflows, such as metadata tagging and data quality checks.
• Collaborate with Enterprise wide Data and Information initiatives to deliver on Otsuka’s Data, AI, reporting analytics, and information utilization, and governance goals.

Qualifications/ Required Knowledge/ Experience and Skills

• Master's or Ph.D. in a quantitative discipline such as Data Science, Bioinformatics, Statistics, Computer Science, or a related field.
• 8-10+ years of experience in data management, data governance, stakeholder management or a related role within the pharmaceutical, biotech, or life sciences industry.
• Proven track record of defining, implementing, and operationalizing data governance frameworks and delivering strategic reporting in a regulated (GxP) environment.
• Deep understanding of R&D data and information domains (e.g., clinical trials, drug development, external real-world data, genomics, and other digital/device and sensor data), data standards (e.g., CDISC), and regulatory compliance.
• Experience collaborating with data science and AI teams and a strong familiarity with the modern data stack (cloud platforms, data lakes, data catalogs).
• Familiarity with modern DSPM, and Data Governance solutions.
• Excellent leadership, communication, and change management skills, with the ability to influence senior stakeholders across a complex, matrixed organization.
• Excellent communication and stakeholder management skills, with the ability to convey complex technical concepts to non-technical audiences.

Pay

Minimum $186,489.00 - Maximum $278,875.00, plus incentive opportunity: The range shown represents a typical pay range or starting pay for individuals who are hired in the role to perform in the United States. Other elements may be used to determine actual pay such as the candidate’s job experience, specific skills, and comparison to internal incumbents currently in role. Typically, actual pay will be positioned within the established range, rather than at its minimum or maximum.