Director, Data Sciences Lead

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OBJECTIVES/

PURPOSE:

The Real World Data Center of Excellence is meant to foster an environment that simplifies and accelerates collaboration-driven insights that enable data driven business decisions by bringing best practices and standardizing approaches to common questions involving real world data. The Director, Real-World Evidence Data Sciences Lead is responsible for managing the acquisition, processing, and curation of non-Takeda sourced observational RWD, including claims, disease registry, labs and electronic health/medical records (EHR/EMR) data.

The role will manage a wide portfolio of data types, with a goal of supporting diverse analyses across Research & Development (R&D); will ensure data transfers follow quality standards; and will coordinate with other stakeholders in R&D to ensure acquisitions satisfy expected analysis plans. In addition, responsibilities include feasibility and exploratory analyses of the RWD, working with observational data sciences colleagues, and collaborating with stakeholders across Takeda, including epidemiologists, translational biologists, biomarker scientists, and biostatisticians.

These analyses will provide a better understanding of disease natural history, incidence/prevalence, co-morbidities, treatment patterns, and health and safety outcomes in ‘real world’ patient populations, across a wide variety of serious and unmet diseases, resulting in a high impact to research and early development, clinical development pipeline, and marketed products.

ACCOUNTABILITIES:

• Develop and implement enterprise RWE strategies to efficiently address business needs.

• Collaborate internally and externally to address RWE needs and advise on unmet data needs

• Strengthen partnerships with stakeholders within the organization and externally with platform vendors, RWE innovators, FDA etc.

• Act as a knowledge developer and repository around observational studies, FDA policies, publications etc related to RWE.

• Be at the forefront of advanced technologies like Gen-AI/agentic AI and their applications of Real-World Data.

CORE ELEMENTS RELATED TO THIS ROLE:

• Collaborate with external vendors, Takeda partners, and external organizations responsible for collecting the data

• Ensure data transfers follow quality standards and coordinate with other stakeholders in R&D to ensure acquisitions satisfy expected analysis plans

• Define and implement data transfer, quality control and curation processes, and maintain the data quality pipeline

• Collaborate with other team members to ensure consistency of quality control methods and processes across disparate types of data sourced external to Takeda

• Conduct analyses pertaining to the application of the observational RWE data for diverse stakeholders, including Epidemiology, Value & Access, Translational Biology, Biomarkers; these include specific epidemiology, health outcomes and other observational studies to better understand disease natural history, incidence/prevalence, co-morbidities, treatment patterns, and health and safety outcomes in ‘real world’ patient populations

• Advise on the associated analyses plans using information developed in the execution of the data quality pipelines

• Ensure information is surfaced to ensure the externally sourced data is fit for purpose

• Develop systems, processes and tools (pipelines) which impact enterprise use of our data assets and confirm data quality

• Lead global organizational RWD transparency and education by delivering learning modules on relevant dimensions for users’ qualifications

DIMENSIONS AND ASPECTS:

Technical/Functional (Line) Expertise

• Comprehensive understanding of the pharmaceutical industry and drug development

• Understand and enable analytic infrastructure, including CFR 11 certified software tools, semi-automated, validated SAS algorithms and a…