Atorus
full-time
remote from anywhere in the U.S.
About The Role
We are seeking a highly skilled Senior Shiny Developer / Full-Stack Data Scientist with a strong background in SAS and CDISC standards who has since transitioned to R-based development. The ideal candidate is comfortable leading end-to-end data pipelines, building interactive Shiny applications, and implementing best practices in data engineering for clinical and regulatory submissions. Key Responsibilities Design, develop, and maintain interactive Shiny applications for clinical data analysis and visualization. Develop and manage data pipelines and engineering workflows, ensuring robust, scalable, and reproducible processes. Collaborate with cross-functional teams on clinical trial data, including CDISC SDTM/ADaM datasets and pharmacometric modeling outputs. Implement best practices for code validation, testing, and governance in R and SAS. Leverage HPC, Linux, and Python environments for large-scale data processing and optional LLM-based analytics. Support regulatory submissions by preparing reproducible analyses and following SOPs. Contribute to the development and maintenance of internal R packages, Pharmaverse tools (Admiral), and submission-ready pipelines. Mentor junior developers and promote best practices in coding, data management, and documentation. Required Qualifications Senior-level experience in Shiny application development and full-stack R programming. Strong SAS experience with CDISC SDTM/ADaM knowledge; experience transitioning SAS workflows to R. Fluency in R for clinical data processing, analysis, and submissions. Experience with data pipelines, engineering, and workflow automation (e.g., HPC, Linux, scheduling). Experience with Posit (RStudio) environment and associated deployment tools. Ability to implement reproducible, validated, and well-documented code. Nice-to-Have / Optional Experience with GxP Experience using Pharmaverse/admiral Python experience, including working with large data sets or LLMs Experience in regulatory submissions or R-based SOPs Experience with interactive dashboards for exploratory data analysis Key Skills & Attributes Strong analytical and problem-solving skills. Ability to work independently while collaborating effectively with cross-functional teams. Excellent communication skills, able to explain complex technical concepts to non-technical stakeholders. Focus on senior-level ownership: proactive, detail-oriented, and committed to best practices.
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We are seeking a highly skilled Senior Shiny Developer / Full-Stack Data Scientist with a strong background in SAS and CDISC standards who has since transitioned to R-based development. The ideal candidate is comfortable leading end-to-end data pipelines, building interactive Shiny applications, and implementing best practices in data engineering for clinical and regulatory submissions. Key Responsibilities Design, develop, and maintain interactive Shiny applications for clinical data analysis and visualization. Develop and manage data pipelines and engineering workflows, ensuring robust, scalable, and reproducible processes. Collaborate with cross-functional teams on clinical trial data, including CDISC SDTM/ADaM datasets and pharmacometric modeling outputs. Implement best practices for code validation, testing, and governance in R and SAS. Leverage HPC, Linux, and Python environments for large-scale data processing and optional LLM-based analytics. Support regulatory submissions by preparing reproducible analyses and following SOPs. Contribute to the development and maintenance of internal R packages, Pharmaverse tools (Admiral), and submission-ready pipelines. Mentor junior developers and promote best practices in coding, data management, and documentation. Required Qualifications Senior-level experience in Shiny application development and full-stack R programming. Strong SAS experience with CDISC SDTM/ADaM knowledge; experience transitioning SAS workflows to R. Fluency in R for clinical data processing, analysis, and submissions. Experience with data pipelines, engineering, and workflow automation (e.g., HPC, Linux, scheduling). Experience with Posit (RStudio) environment and associated deployment tools. Ability to implement reproducible, validated, and well-documented code. Nice-to-Have / Optional Experience with GxP Experience using Pharmaverse/admiral Python experience, including working with large data sets or LLMs Experience in regulatory submissions or R-based SOPs Experience with interactive dashboards for exploratory data analysis Key Skills & Attributes Strong analytical and problem-solving skills. Ability to work independently while collaborating effectively with cross-functional teams. Excellent communication skills, able to explain complex technical concepts to non-technical stakeholders. Focus on senior-level ownership: proactive, detail-oriented, and committed to best practices.
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