R Developer

The incumbent provides technical leadership and project management for the development of end to end innovative analytic and reporting web applications, used across the global biostatistics & programming (B&P) user community. Reporting to the Global Head of Analytics and Reporting Tools (ART), and with the support of senior ART team members located across the world, the incumbent leads development, maintenance, and release of R packages and RShiny applications in production with quality and in a timely manner, following regulatory requirements. The incumbent applies hands-on technical expertise in R and Shiny, combined with clinical trial, statistical analysis, APIs, devops tools, Docker/Kubernetes, and cloud environment knowledge to succeed in the development and deployment of innovative statistical reporting solutions. The incumbent serves as a department level expert to interact with IT and support companywide initiatives that have impact on technology related processes, as well as a mentor and train junior level team members and internal resources.,

• Work with ART team members, Statistical programmers and Statistician on the development, maintenance, and support of innovative R packages and Shiny applications to support Statistical Analysis on global clinical trial projects.
• Collaborate with IT, standard governance, and Quality Assurance for the deployment in production of global innovative reporting applications on premise or in the cloud.
• Ensure proper documentation, validations and ensure support is in place for each application following our SOP and regulatory requirements.
• Train / Mentor junior ART team members on R package and Shiny application development
• Ensure training material and user guide are available for each application.
• Provide technical guidance to project teams and users on all matters involving ART applications and tools as needed.
• Support department initiatives and task forces. Lead/participate in departmental or cross-functional working groups and process improvement activities.
• Identify areas for improvement and recommend solutions related to systems, reporting tools, technologies, and best programming practices.
• Actively participate in department working groups, provide input in development of tools applicable to process improvement.
  
  Advanced degree in Statistics, Computer Science, Mathematics, Engineering, Life Science, or related field, with +5 years of web application development experience
• Excellent technical skills with R
• Strong knowledge in frontend development: Shiny, JavaScript, Vue.js, Jinja.
• Demonstrated experience and strength in developing, maintaining, and deploying web applications and APIs
• Demonstrated experience with DevOps tools such as GitHub, GitLab, Jira, Confluence, CI/CD.
• Proven experience with relational and non-relational database such as MySQL, Postgres, MongoDB. Extra points for Graph Databases
• Demonstrated experience with Computer System Validation in a regulated environment.
• Proven experience in the development and execution of project charter, user requirements, functional and design specifications, validation plans, development and implementation, agile software development.
• Excellent project management skills. Ability to effectively organize and manage multiple assignments with challenging timelines
• Good understanding of drug development and statistical reporting process
• Good Knowledge of CDISC standards.
• Good understanding of regulatory requirements concerning electronic submission.
• Strong understanding of pharmaceutical clinical development (i.e., understanding of statistical concepts, techniques, and clinical trial principles).
• Collaborative teamwork and interpersonal skills that demonstrate initiative and motivation. Strong problem-solving skills. Excellent verbal and written communication skills in a global environment.
• Experience in collaboration with external partners and/or vendors.
• Ability to estimate resource requirement.
• Strong communication skills
• Extra points for working experience mixing Python and R and with JavaScript, Pandas, NumPy/SciPy, ML package Scikit-learn, and visualization libraries such D3.js, DC
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