Turn a group of data practitioners into a reliable, production-ready ML team.

Standardize best practices, reduce technical debt, and support your team with trusted guidance — from the people who build and maintain scikit-learn.

Get practical guidance for your team

What Data Science Team Leads rely on Probabl for?

Probabl is the official steward of the scikit-learn ecosystem, operated by contributors and maintainers. We help teams use scikit-learn the way it was designed to be used — across projects, people, and time.

We don’t replace your tools.
We help your team use them the way they were designed to be used — across projects, people, and time.

Our work is grounded in:
• how scikit-learn is meant to be used in practice
• ML practices that scale beyond individual notebooks
• open-source, vendor-neutral principles
• long-term maintainability over shortcuts

👉 Get practical ML guidance

👉 Get your team certified

Because you are accountable for more than models

As a Data Science Team Lead, you don’t just deliver models — you shape how machine learning is done across your team. Probabl helps you turn that responsibility into leverage.

Get expert guidance when your team needs it.

• Helpdesk for day-to-day technical questions with a clear SLA
• Masterclasses for continuous learning of your team and best practices for shared standards
• On-demand Expert guidance on your hot topics such as: pipeline design, experimentation practices, model evaluation, deployment and monitoring handoffs

Get Probabl Support

Align and validate your team’s skill level.

• Certification for Data Scientists
• Hands-on, theoretical and applied evaluations
• Shared baseline for best practices
• Objective signal for internal and external stakeholders

Certify your team

When your team moves beyond individual notebooks

Two ways to extend your team’s ML practice beyond experimentation.

From prototype to production-grade ML

Hands-on support to turn promising work into systems you can rely on.
• Audit · Ideate · Experiment · Scale
• Real systems, not slides
• Open-source, vendor-neutral

Explore our Forward Deployed Engineer program

Inspect and reason about model behavior

Make model behavior explicit — for your team and stakeholders.
• Evaluation beyond single metrics
• Clear comparisons and diagnostics
• Built for scikit-learn workflows

Explore Skore

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