Companies that use Stan
A state-of-the-art platform for statistical modeling and high-performance statistical computation. Used for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.
11,068
companies
List of companies using Stan
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"stan\"
]
}"Technology
is any of
Stan
Employees9IT Services and IT ConsultingStanHigh confidence
Employees560kRevenue$24BRestaurantsStanHigh confidence
Employees284Technology, Information and InternetStanHigh confidence
Employees834Revenue$1.4BConstructionStanHigh confidence
Employees51Hospitals and Health CareStanHigh confidence
Employees155kRevenue$224BRetailStanHigh confidence
Employees10kTransportation, Logistics, Supply Chain and StorageStanHigh confidence- RetailStanHigh confidence
Employees70kRevenue$14BBusiness Consulting and ServicesStanHigh confidence
Employees9kRetailStanHigh confidence
We have data on 11,068 companies and users that use Stan. Our Stan users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
How to target Stan users
- How to customize this list?
You can customize this data to your needs by filtering for geography, industry, company size, revenue, technology usage, job postions and more. You can download the data in Excel or CSV format.
- How to be alerted when companies adopt this technology?
You can get alerts for this data. You can get started by selecting the technology you are interested in and then you will receive alerts in your inbox when there are new companies using that technology.
- How to import this data to my CRM?
You can export this data to an Excel file, which can be imported into your CRM. You can also export the data to an API.
Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Stan is a powerful open-source probabilistic programming language widely used in the realm of Machine Learning Tools. It empowers users to specify complex Bayesian models through concise and intuitive syntax, enabling them to perform sophisticated statistical analyses with ease. Stan's versatility allows it to handle a variety of models, from simple linear regressions to intricate hierarchical models, making it a popular choice among data scientists and researchers.
Founded in 2012 by Andrew Gelman and his team at Columbia University, Stan originated from the need for a more efficient and scalable platform for Bayesian modeling. Motivated by the limitations of existing tools, they set out to create a language that combined the flexibility of probabilistic programming with the speed of modern computing. This led to the development of Stan, which quickly gained traction within the data science community.
In the current market, Stan holds a significant share within the Machine Learning Tools category, owing to its robust capabilities and user-friendly interface. As the demand for advanced statistical analysis continues to rise across industries, the outlook for Stan appears promising. With ongoing updates and improvements, it is anticipated that Stan's market share is likely to experience further growth in the future as more organizations recognize the value of robust Bayesian modeling tools in their data-driven decision-making processes.