Senior Director, Data Engineering

Position Summary

Data Technologies and Analytics Solutions (DTAS) in Data & Analytics (D&A) is an organization comprised of multiple functional teams. The remit of the Senior Director, Data, AI, and Software Engineering position will have responsibilities to lead and continue to evolve this technically focused team while collaborating and leveraging the adjacent functions: Data Science Solutions and the DTAS Liaisons.

The Data, AI and Software Engineering team will focus on the software development (design and coding), system design, testing and debugging, deployment, and maintenance needs of the DTAS portfolio in support of Otsuka’s Development, Commercial, Corporate function, and Enterprise goals. This team is a centralized capability and comprises of programmers, full-stack software developers, and data engineers who, aligned with Otsuka IT, design, create/code, test, deploy, manage and maintain fit for purpose across both, COTS and custom built solutions as well as working with other D&A pillars to enable data collection, curation, quality, consolidation, preparation, testing, deployment, access, and maintenance of databases. The Data, AI and Software Engineering team will provide support across R&D, Corporate Functions and select advanced analytics support to Commercial Analytics. This team will also be critical to supporting OAPI/OPDC AI Enablement through the AI Council and enterprise AI use cases.

This role oversees computer scientists, programmers, data and full-stack engineers and architects who deliver technical capabilities in an integrated manner to support the broad Otsuka portfolio.

Reporting to the E.D., Data Technologies & Analytics Solutions, this leader will become a driving force of change, cross-functional collaboration, impactful innovation, quality, and delivery across the OAPI/OPDC organization.

Key Job Responsibilities

• Provide leadership, oversight and operational/technical/strategic direction to the Data, AI and Software Engineering team that is aligned to the broader Otsuka strategic plan and achievement of Corporate Goals.
• Through collaboration with other D&A and DTAS pillars and cross-functional partners, a high functioning Data, AI, and Software Engineering team would be expected to:
  • deliver leading edge engineering approaches, effective enterprise 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.
  • development and deployment, access, and maintenance of databases.
  • development, deployment, and product management of business enabling applications.
  • provide modernized reporting, visualization, and modeling of data/information to enable business partners to assess and monitor indicators of performance, quality and risks as well as provide predictive and prescriptive insights.
  • suitable, essential, high-quality, auditable, and robust architecture and engineering solutions with a focus on operational excellence.
  • digital data solutions from an innovation hub established by DTAS involving a lean data and digital analytics incubation approach to explore, experiment, and rapidly deploy emerging tools from both within and outside our industry, thereby positioning Otsuka to take advantage of potential disruptions in the marketplace.
• Contributes to the rolling Strategic Plan and corresponding roadmap for DTAS.
• Accountable to awareness and exploration of external landscape and emerging data technologies and trends in partnership across DTAS, D&A and IT stakeholders. Developing business cases, inclusive of ROI, designed to bring modern approaches forward and advocate for new data tools and technologies that will position internal stakeholder to deliver with industry-leading instruments.
• In support of multiple domain portfolios and strategies, such as Clinical Development, Commercial, HR, Ethics & Compliance, and Legal Affairs. In partnership with the other DTAS leaders, this leader will ensure portfolio prioritization is consistent with the enterprise imperatives and that there is the necessary domain expertise within their organization.
• Working with other DTAS leadership, evolve the demand management for DTAS in consideration of the inputs and requirements of key stakeholders, vendors, and broad organizational objectives to ensure needs are met in a timely and effective manner.
• Operational excellence would be demonstrated through effective and efficient delivery across the multiple portfolios supported by the DTAS organization. This includes but is not limited to the resourcing, prioritization, timeline management, functional o