Director, Real-World Evidence Data Sciences Lead

Role Summary

The Director, Real-World Evidence Data Sciences Lead is responsible for managing the acquisition, processing, and curation of non-Takeda sourced observational real-world data (RWD), including claims, disease registries, labs, and EHR/EMR data. The role supports a wide portfolio of data types to enable diverse analyses across Research & Development, ensures data transfers meet quality standards, and coordinates with stakeholders to satisfy analysis plans. It includes feasibility and exploratory analyses of RWD and collaboration with epidemiologists, translational biologists, biomarker scientists, and biostatisticians to enhance understanding of disease natural history, treatment patterns, and health outcomes in real-world populations, contributing to research, early development, and product pipelines.

Responsibilities

• 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, and regulatory bodies.
• Act as a knowledge developer and repository around observational studies, policies, and publications related to RWE.
• Be at the forefront of advanced technologies like Gen-AI/agentic AI and their applications to Real-World Data.
• Collaborate with external vendors and partners responsible for data collection; ensure data transfers meet quality standards.
• Define and implement data transfer, quality control, and data curation processes, and maintain the data quality pipeline.
• Ensure consistency of quality control methods across disparate data types sourced externally.
• Conduct analyses of observational RWE data for stakeholders (epidemiology, value & access, translational biology, biomarkers) to understand disease history and outcomes.
• Advise on analysis plans derived from data quality pipelines; ensure data is fit for purpose.
• Develop systems and tools (pipelines) that enhance enterprise use of data assets and verify data quality.
• Lead global RWD transparency and education by delivering learning modules for user qualification.

Qualifications

• 5–8 years of relevant experience focusing on clinical, observational, or RWE data management, ingestion, curation, and analysis.
• Experience establishing and managing relationships with external vendors and organizations for acquisition of observational RWD.
• Deep understanding of drug development and the biopharmaceutical industry, with emphasis on RWE data.
• Experience using hardware and software used to curate, process, and analyze data.
• Experience with scripting/coding languages (R, Python, Unix scripting, etc.).
• Knowledge of data analysis, trending, and statistics; experience developing and implementing data standards.
• Strong project management skills and ability to lead, collaborate, and communicate across diverse observational RWE stakeholders (scientific, technical, operational).
• High attention to detail and ability to manage multiple competing priorities; proven ability to establish and manage effective business relationships with internal and external stakeholders.

Skills

• Scripting and programming: R, Python, Unix scripting
• Data curation, quality standards, and data pipeline development
• Analytical thinking and statistical knowledge for real-world data analyses
• Strong communication and leadership across functions, regions, and external partners
• Strategic collaboration with epidemiology, translational biology, biomarker science, and biostatistics

Education

• Advanced degree in Computer Science, Data Science, Life Sciences, Epidemiology, Bioinformatics, Clinical Informatics, or similar technical field