R​/Rshiny Developer Clinical Data

We are seeking a skilled R / RShiny Developer with expertise in the clinical data domain. You will contribute to the transformation of how we deploy analytics tools using cloud-native architecture, focusing on scalable, reliable, and automated R analytics and data science products. Be part of a team where your expertise in R and RShiny will have a direct impact on accelerating the discovery and delivery of life-changing therapies.

• Design, build, and deploy advanced RShiny applications on cloud platforms, ensuring they are scalable and performant for large-scale clinical data analysis.
• Collaborate with data scientists, biostatisticians, and research teams to create sophisticated RShiny applications that drive our clinical data analysis efforts.
• Utilize tools like Posit Workbench, Posit Connect, and AWS services to create workflows that support the deployment of R-based analytics applications.
• Develop and maintain robust data pipelines to pull, process, and visualize large datasets from data sources (Databricks) within RShiny applications.
• Work closely with data engineers and architects to ensure the seamless integration of data sources (Databricks) and tools used within the organization.
• Create and maintain technical documentation to support ongoing development and deployment processes.

• Minimum of 5 years of experience in the IT industry, with a strong emphasis on data visualization and dashboard development, particularly using R.
• Proven experience in the Life Sciences, Biotech, or Pharma industry is a must.
• Bachelor's degree in computer science, Engineering, Information Systems, Data Science, or a related field is required. A master's degree is preferred.
• 3+ years of hands-on experience with R, R packages, RStudio, and RShiny, particularly in the context of clinical data analysis.
• 2+ years of experience in building and maintaining CI/CD tooling (e.g., Gitlab, Git Hub).
• Basic knowledge of SQL for querying databases and manipulating data within both relational databases and big data environments.
• Experience in integrating RShiny applications with various data sources, particularly cloud-based data storage solutions like AWS S3, Azure Data Lake, or similar platforms.
• Advanced Shiny Techniques:
  Proficiency in using shiny modules, JS events, and custom bindings to extend the functionality of Shiny applications.
• User-Centric Design:
  Strong ability to implement visually appealing and user-friendly applications using HTML/CSS.
• Ability to scale Shiny applications to hundreds of users, with experience in performance optimization at various levels (frontend, backend, infrastructure).

• Validation and Compliance
  :
  Experience in validating RShiny applications to meet regulatory standards such as FDA, EMA, and GxP guidelines. This ensures that the applications are reliable, secure, and compliant with industry regulations.
• Open Source Contributions
  :
  Active participation in the open-source community, particularly in developing and maintaining R packages and Shiny applications. This demonstrates a commitment to continuous learning and staying updated with the latest advancements in the field.
• Performance Optimization
  :
  Expertise in optimizing the performance of Shiny applications, including frontend, backend, and infrastructure levels, to ensure they can handle large datasets and multiple users efficiently.
• User Behavior Analysis
  :
  Ability to analyze user behavior and interactions with Shiny applications to improve usability and functionality. This involves understanding the diverse needs of users ranging from data scientists to clinicians.
• Data Integration
  :
  Proficiency in integrating Shiny applications with various data sources, including cloud-based storage solutions like AWS S3, Azure Data Lake, and other platforms.