Principal R Programmer - R Shiny Development

JOB DESCRIPTION

We are hiring a remote R/Shiny Developer to work directly with a pharma company’s internal team leading project efforts and providing support. This position reports to the Director of Biostatistics in FSP Services business unit in Cytel.

RESPONSIBILITIES

The R/Shiny developer will program using R software to perform statistical analysis. They also should be familiar with creating Shiny applications in R. The programmer will be responsible for mapping access to several databases of varying types (e.g. SAS, ASCII, etc.). Programming activities will be in support of research and exploration as well as for clinical trial analysis or publications. Though the majority of programming activities require R software, the programmer will also be required to utilize the SAS software system; they should be proficient in SAS/BASE and SAS/STAT packages. As the area of focus is the Pharmaceutical / Biotechnology domain, the programmer will be tasked with mapping data into CDISC formats following the data structures and controlled terminology.

If the programmer is delegated as a lead, there may be additional responsibilities for monitoring and meeting assigned program milestones as well as leading a small team of statistical in-house or consultant programmers to accomplish tasks. Essential functions include creating systems that assist the Statistical Programming staff and Biostatistical staff to create tables, data listings, graphs, and analysis for final reports, abstracts, posters, manuscripts, and other clinical publications; developing systems to support electronic regulatory submissions; providing systems and support for clinical data management staff, clinical programmers, quality control (QC) staff, and biostatisticians; producing and supporting systems that extract data from the clinical database; and building analysis databases composed of SAS datasets.

The R/Shiny developer must follow established standardized design and programming procedures; provide mentoring to junior level Programmers; assist in establishing standardized programming procedures and work instructions; develop, enhance, evaluate, and validate standardized macros and utility programs; ensure that regulatory requirements are met through validation/compliance activities; and develop and maintain clinical processing work flow systems.

The R/Shiny developer may work in an independent environment and drive research into the data, thus having a statistical background is an advantage.

QUALIFICATIONS

Qualifications and Experience:

• Minimum Education: BS or MS degree in Computer Science, Statistics, or related health science field.
• Minimum Work Requirements:
  • Must have hands-on working experience with R code development & R-Shiny.
  • At least 5 years of R/SAS programming experience with clinical trial data.
  • General knowledge of regulatory requirements and drug development process. Experience working with CRO/Pharma industry.
• Skills: Excellent organizational skills and good verbal and written communication skills. Ability to work independently is required. High attention to detail including proven ability to manage multiple, competing priorities. Candidate must possess strong project management and problem-solving skills, with the ability to effectively lead and collaborate with all departments & team members.

Technical Expectations:

In addition to a deep understanding of base R programming skills, the Intermediate programmer should be able to:

• Know when to write a function to simplify coding.
• Understand the family of “purrr” functions to avoid unnecessary loops and write cleaner code.
• Know their way around the Tidyverse: Learn and drill the major techniques from the following packages: readr, dplyr, tidyr, stringr, purrr, forcats, lubridate, and ggplot2.
• Create advanced graphics using ggplot() and ploty() functions.
• Demonstrate proficiency in R/Shiny. Knowledge of golem, HTML, and Javascript would be helpful for developing R/Shiny applications.
• Create documents using R/Markdown.
• Make an R package and have strong experience in R package development.
• Document code using roxygen to clearly explain the use of created functions.
• Perform various statistical analyses using R.
• Validate sections of code using testthat.
• Test if two objects (vectors, lists, data frames) are identical or not.
• Use Git bash or Git for Windows to stow and retrieve code from a GitHub Repository.