Description
R Developer
Brentford/Remote
Contract: 3 Month (ASAP Start)
Pay: up to £564/d (Inside IR35 - via Umbrella ONLY)
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 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.
Responsibilities:
Work with existing team to optimise and deploy shiny based web applications.
Assist in the roll out of shiny web applications.
Conduct and support knowledge transfer and working sessions with offshore analytics teams.
Mentor and upskill more junior members of the team.
Requirements:
- 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, eg 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 life cycle, 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 R