Associate Director, Statistical Programming - R Implementation

The purpose of this job is to provide statistical programming technical support related to R programming, R related system and technology. Develop and drive R programming, package, and R shiny app development. Lead the R programming implementations. Represent programming in DS external collaborations on R technology and capabilities.

Lead/contribute to DS R programming system technology development: Lead/contribute to the R programming system development. Act as R programming SME and functional representative of R systems and infrastructure to identify system and technology development needs and to define functional requirements. Provide technical guidance to the development. Lead and may approve UATs. Lead/contribute to resolutions of BDM departmental (internal and external) R related analysis and programming technical issues and difficulties. Lead the trainings and implementations of R system and programming technology. Developing R package and Shiny apps: Contribute to strategy of R programming innovation to support BDM analysis and reporting, such as R shiny apps for data surveillance, visualization, modeling and simulations, and safety signal detection. Lead the development and validations of R package and/or shiny apps. Identify and build the use cases and process/resources to guide the implementations. Lead, advocate and nurture R programming innovation globally within DS. Represent the programming innovation outside of DS and establish the company reputations and images. Develop study specific shiny apps or execute shiny apps at study level. Publish shiny apps for study or against integrated database Representing cross-functional collaborations on R capabilities and systems: Collaborate with RD non-BDM and non-RD R user group or developers. Collaborate with biostat innovation to enhance BDM overall R capabilities and implementations. Collaborate with CSPV to enable/effectively support safety signaling detections and across compounds safety reviews (i.e., ILD). Collaborate with Clinical Development and Clinical Sciences for effective data surveillance

Education Qualifications
Bachelor's Degree an accredited institution in a science or in a technical field such as computer science or mathematics required Master's Degree preferred

Experience Qualifications
10 or More Years Bachelor’s degree with minimum 10 years (or Master’s degree with minimum of 7 years) proven experience required
7 or More Years Previous experiences in R programming area, involved in R and/or Shiny app development and implementation. required
Advanced working knowledge of all aspects of the R and SAS programming language used in clinical trials programming. required
Advanced working knowledge of CDISC SDTM and ADaM, and extensive experiences of their implementation in clinical trials analysis required
Advanced understanding of statistical concepts in support of analyses and reporting of clinical trials. required
Having knowledge of all phases of drug development, including early and late phase clinical development and submission required
Having solid background of applied statistics required
Solid knowledge of new advanced statistical methods using SAS or R required
Advanced knowledge in database structures and set-up required


Travel Requirements
Ability to travel up to 10% of the time.