7 of 7 Shiny Jobs in the UK excluding London

Data Services, Fabric, Synapse, or related cloud technologies is highly desirable. Proven ability to create interactive data visualizations using tools like Plotly/Dash, Shiny, Tableau, or Power BI. Experience in developing web applications for data insights using JavaScript, CSS, or similar frameworks is a plus. Knowledge of Generative More ❯

including some or all of the following: Pentaho Business Analytics, SAS Enterprise Guide/Enterprise Miner, SAS Visual Analytics, PowerBI, R Studio and R Shiny Data quality tools such as SAS Data Management Studio Data Fabric tools, including some or all of the following: Pentaho Data Integrator and Talent More ❯

including some or all of the following: Pentaho Business Analytics, SAS Enterprise Guide/Enterprise Miner, SAS Visual Analytics, PowerBI, R Studio and R Shiny Data quality tools such as SAS Data Management Studio Data Fabric tools, including some or all of the following: Pentaho Data Integrator and Talent More ❯

services Skilled in least one of the following to develop custom geospatial applications, including Esri APIs where relevant: Python, JavaScript, SQL, and R/Shiny Proficient in utilising Microsoft Azure services for cloud-based solutions (or similar) Successfully leading a small team to deliver technical tasks and geospatial services More ❯

Programming (ideally in the context of package development). Git and general code-management/documentation practices. Continuous improvement and continuous delivery practices. R Shiny & R Markdown. In addition, you may have experience of some of the following: Automated build and deployment pipelines. Automated test frameworks. Accessing external APIs More ❯

Programming (ideally in the context of package development). Git and general code-management/documentation practices. Continuous improvement and continuous delivery practices. R Shiny & R Markdown. In addition, you may have experience of some of the following: Automated build and deployment pipelines. Automated test frameworks. Accessing external APIs More ❯

ML Studio and Azure DevOps. Effective Communication: Present findings clearly through visualisation and reporting, including interactive dashboards and web applications using Power BI, R Shiny, or Python Flask. MLOps Maintenance: Maintain and enhance MLOps pipelines, focusing on model robustness and performance. Project Tracking: Manage code and project tracking using … reshaping using SQL, R/Tidyverse, and Python/Pandas. visualisation Expertise: Experience with data visualisation tools and frameworks such as Power BI, R Shiny, and Python Flask. Agile Methodology: Familiarity with Git and Azure DevOps for version control and agile task management. Statistical Acumen: Solid understanding of statistical More ❯