Domino for Data Scientists
Become a Data Science Superhero
As a data scientist, it is frustrating to lack the infrastructure and tools you need, spend lots of time on tedious DevOps tasks, and search for work you know others have already done. You need freedom and flexibility to work with peers, do your best work, and become a data superhero in your organization.
Domino's MLOps platform gives you the flexibility and freedom to support what you do best – explore, experiment, and solve complex business problems – and abstract away the technical hurdles that slow you down.
With self-serve access to preferred tools and compute, automatic reproducibility, and repeatable workflows to manage, develop, deploy, and monitor models at scale, Domino will make you more productive and amplify the impact of your work.
Freedom to Use the Latest Tools
Test new ideas quickly using any tool, package, or language in an integrated environment that eliminates distractions.
Access to Scalable Infrastructure
Get one-click access to GPUs and distributed compute frameworks for deep learning jobs and other complex projects.
Confidence in Deployed Models
Automatically monitor models in production for data drift and quality, then easily retrain and rebuild models as needed.
Find past work, reproduce results, and collaborate with peers to push past blockers and unlock breakthroughs.
Recommended Resources for Data Scientists
Domino Data Science Blog
Our popular blog is a regular stop for data scientists who want to keep-up-to-date on all of the latest techniques, tools, and best practices – to accelerate their work and their careers.
Pump Up Data Science Productivity with a Modern Workbench
Understand the unique workbench capabilities that Domino provides to maximize productivity.
The Pros and Cons of Spark in a Modern Enterprise Analytics Stack
Get an overview of Spark’s strengths and weaknesses in the context of data science and machine learning workflows.