Director, Data Science at a manufacturing company with 10,001+ employees
Real User
Top 10
Apr 3, 2026
My main use case for Posit is data science workflows, automation, and using it for model building and data exploration. A specific example of how I use Posit for model building and automation in my workflow is that we use it for a forecasting model for retail customers to estimate the effects on volume of changing any number of input levers such as price, distribution, or promotion activities.
Sr. Scientist at a pharma/biotech company with 10,001+ employees
Real User
Top 20
Mar 12, 2026
My main use case for Posit involves coding, executing, and deployment. A quick specific example of how I use Posit for coding, executing, or deployment is coding in R and running it on Posit Workbench. I typically run all kinds of projects or analyses on R through Posit Workbench, mostly associated with multi-omics datasets, including data science, statistical analysis, and reporting.
My main use case for Posit is to support data science teams by managing and maintaining Posit platform infrastructure. For example, I work as an administrator at Posit Workbench and Posit Connect environments, ensuring that they are stable, scalable, and accessible for users who run R and Python workloads, while also managing deployment, monitoring, and troubleshooting of applications hosted on Posit Workbench. Our users primarily run data science and analytics workloads using both R and Python on Posit. Typical workloads include statistical analysis, data exploration, and building predictive models. A common workflow involves data scientists using Posit Workbench to analyze large datasets, develop models in R or Python, and publish results as dashboards or APIs through Posit Connect, which could be interactive Shiny applications or Quarto reports or Python-based APIs that help teams visualize insights or automate parts of the analysis process. Our team interacts with Posit not just from the user perspective, but also from the platform operations standpoint. We manage the infrastructure, ensure high availability, and monitor performance so that data scientists can focus on their analytical tasks without worrying about the underlying environment, particularly since they are also working on drug discovery. I belong to the pharma domain, so Posit is very useful for them. We also support deployment workflows, help troubleshoot issues, and integrate Posit with other enterprise systems such as authentication services and cloud infrastructure, ensuring the platform is reliable, secure, and scalable for all users.
Electrical Engineer Ii at a healthcare company with 10,001+ employees
Real User
Top 20
Feb 19, 2026
My main use of Posit is to deploy Python Flask applications for internal use of tools within our company. I deployed a search query and engine that scientists can use to access a database, query results of research literature that is out there, and run an AI model on these results to help them create better systematic reviews.
I use Posit for both Posit Connect and Posit Workbench. The Workbench is used for development, as there are many packages not supported by RStudio because I didn't have RStudio Pro. Posit Connect is used to host applications, such as the R application and R Shiny application, connecting to Azure SQL and database instances.
Our primary use case for Posit involves end-to-end data processing. We start by pulling data from various sources like CSV, Excel, Snowflake, and Databricks. We clean the data, analyze it, and visualize it using tools like ggplot, Shiny dashboards, or R markdown documents. We also use Posit for building models and sharing findings for better insight within the team.
We use Posit to deploy applications developed in R and Python. Our team creates applications and models, which they then host on GitHub. We assist them in deploying these models and provide the necessary access and support.
Posit offers data analysis and visualization tools designed to enhance decision-making through actionable insights. It supports diverse programming environments and integrates seamlessly, facilitating efficient data processes for teams in analytics-driven sectors.Posit elevates analytical operations by providing powerful tools for data management and visualization. Its adaptive nature enables integration with several programming languages, catering to the needs of data professionals seeking...
My main use case for Posit is data science workflows, automation, and using it for model building and data exploration. A specific example of how I use Posit for model building and automation in my workflow is that we use it for a forecasting model for retail customers to estimate the effects on volume of changing any number of input levers such as price, distribution, or promotion activities.
My main use case for Posit involves coding, executing, and deployment. A quick specific example of how I use Posit for coding, executing, or deployment is coding in R and running it on Posit Workbench. I typically run all kinds of projects or analyses on R through Posit Workbench, mostly associated with multi-omics datasets, including data science, statistical analysis, and reporting.
My main use case for Posit is to support data science teams by managing and maintaining Posit platform infrastructure. For example, I work as an administrator at Posit Workbench and Posit Connect environments, ensuring that they are stable, scalable, and accessible for users who run R and Python workloads, while also managing deployment, monitoring, and troubleshooting of applications hosted on Posit Workbench. Our users primarily run data science and analytics workloads using both R and Python on Posit. Typical workloads include statistical analysis, data exploration, and building predictive models. A common workflow involves data scientists using Posit Workbench to analyze large datasets, develop models in R or Python, and publish results as dashboards or APIs through Posit Connect, which could be interactive Shiny applications or Quarto reports or Python-based APIs that help teams visualize insights or automate parts of the analysis process. Our team interacts with Posit not just from the user perspective, but also from the platform operations standpoint. We manage the infrastructure, ensure high availability, and monitor performance so that data scientists can focus on their analytical tasks without worrying about the underlying environment, particularly since they are also working on drug discovery. I belong to the pharma domain, so Posit is very useful for them. We also support deployment workflows, help troubleshoot issues, and integrate Posit with other enterprise systems such as authentication services and cloud infrastructure, ensuring the platform is reliable, secure, and scalable for all users.
My main use of Posit is to deploy Python Flask applications for internal use of tools within our company. I deployed a search query and engine that scientists can use to access a database, query results of research literature that is out there, and run an AI model on these results to help them create better systematic reviews.
I use Posit for both Posit Connect and Posit Workbench. The Workbench is used for development, as there are many packages not supported by RStudio because I didn't have RStudio Pro. Posit Connect is used to host applications, such as the R application and R Shiny application, connecting to Azure SQL and database instances.
Our primary use case for Posit involves end-to-end data processing. We start by pulling data from various sources like CSV, Excel, Snowflake, and Databricks. We clean the data, analyze it, and visualize it using tools like ggplot, Shiny dashboards, or R markdown documents. We also use Posit for building models and sharing findings for better insight within the team.
We use Posit to deploy applications developed in R and Python. Our team creates applications and models, which they then host on GitHub. We assist them in deploying these models and provide the necessary access and support.