Job description Posted 20 August 2021

R Developer

Contract until January 2022

Remote / Brentford

Up to £525 per day via umbrella


An experienced R developer required to support the roll out of a new global RGM market partition

shiny web application. The Repeatable Growth Model (RGM) is the GSK top priority strategic

framework, it is aimed at codifying a repeatable path to drive growth across our business. At the heart of each RGM is the market partition which analyse the market dynamics between our brands and consumers in order to devise targeted marketing objectives and strategies.

The CH Data Science Team is currently developing and deploying a shiny based web application to

conduct the market partition processes. You will be working with our Senior Data Scientist to develop and with the wider Engineering Team to deploy the web application.


·      Work with existing team to optimise and deploy shiny based web applications.

·      Assist in the roll out of shiny web applications to wider GSK.

·      Conduct and support knowledge transfer and working sessions with offshore analytics teams.

·      Mentor and upskill more junior members of the team.



·      MSc or higher degree in STEM subject.

·      At least 5 years of R development.

·      At least 3 years of experience in developing and deploying enterprise grade shiny  applications.

·      Have an excellent and broad knowledge of popular R packages, e.g. tidyverse, Rcpp, parallel etc

·      Can conceptualise, formulate, prototype and implement algorithms to solve business  problems

·      Proven ability to review, refactor and optimise legacy R codes.

·      Proven extensive experience of software development and deployment lifecycle, especially CICD pipelines

·      Good understanding of UX/UI design principles.

·      Experienced in Agile methodologies

Nice to have:

·      Experience with Docker and Kubernetes.

·      Experience with cloud platform, particular Azure.

·      Knowledge of Cpp, CSS, HTML, JavaScript, and jQuery.

·      Experience in machine learning techniques such as dimensionality reduction.

·      Experience in building and deploying machine learning models.

·      Experience in parallel computing with