Manager, Biostatistics, DI-COE- RWE Real World Evidence

Join a Legacy of Innovation 110 Years and Counting!

Daiichi Sankyo Group is dedicated to the creation and supply of innovative pharmaceutical therapies to improve standards of care and address diversified, unmet medical needs of people globally by leveraging our world-class science and technology. With more than 100 years of scientific expertise and a presence in more than 20 countries, Daiichi Sankyo and its 16,000 employees around the world draw upon a rich legacy of innovation and a robust pipeline of promising new medicines to help people. Under the Group's 2025 Vision to become a "Global Pharma Innovator with Competitive Advantage in Oncology," Daiichi Sankyo is primarily focused on providing novel therapies in oncology, as well as other research areas centered around rare diseases and immune disorders.

Job Description:

• Secondary Data Study Protocol Development, Statistical Analysis Plan (SAP), Statistical Analysis, Results Interpretation, and study report: Supports statistical activities for studies including study design, protocol development, SAP development, analysis files development, statistical analysis accuracy validation, results interpretation, and study report input and review. Acts as main statistical contact for the assigned studies and projects. Works effectively with the study team to support and provide the planned deliverables.
• Real-World Evidence (RWE) Activities: Provides guidance in scientific and statistical aspects of RWE activities and support deliverables to ensure quality. RWE activities include the real-world data (RWD) inquiries, RWD/E consultation, and the feasibility assessment using the secondary data. Works closely with the business partner to support and provide the planned deliverables.
• Excellent Communication: Works effectively with the customers/stakeholders and clearly communicates the statistical and scientific input in the design, conduct, analysis, and results interpretation.
• RWE Analytics: Fosters new methodology and provides innovative analytics technique method (e.g., External Control Arm, machine learning, predictive model).

Qualifications:

Successful candidates will be able to meet the qualifications below with or without a reasonable accommodation.

Education Qualifications:

• PhD in Statistics or Biostatistics or pharmaco-epidemiology or other related field preferred
• Master's Degree in Statistics/Biostatistics or pharmaco-epidemiology or other related field preferred

Experience Qualifications:

• 4 or more years relevant experience in the pharmaceutical industry with Ph.D preferred
• 4 or more years with Masters preferred