R specialists for your dedicated team.

Where R fits in a long-term product team.

R exists because statisticians wrote it for themselves. That shows in how directly statistical ideas map onto code, and in the depth of its package ecosystem for methods that have no equivalent elsewhere. For time series, survival analysis or econometrics, an analyst in R is frequently faster than the same analyst in a general-purpose language.

It shows equally in what R is not. Production deployment, long-running services and large engineering codebases are not what the language was built for. The common pattern is analysis in R and delivery in something else, and being explicit about that boundary early avoids an argument later.

What your dedicated team does with R.

Analysis in R runs on a steady rhythm, alongside the sprint cycle. Questions come from the business, the work is investigative, and the output is a decision. That suits a standing assignment far better than a project, because most of the value is in knowing the data already.

The recurring failure is that the analysis is sound and the data underneath it is not. In that case, the right move is to fix the pipelines first with a dedicated data engineering team, and model on solid data after.

Common R use cases.

• Statistical work with a defensible method Analysis where the method stands up to scrutiny, beyond a number that merely looks plausible.
• Experiment and test design Sizing, power and analysis for tests whose result will change a decision.
• Regulated or reported analysis Work that has to be reproducible from raw data to published figure, months after it was run.

Adding R skills to your team.

R capacity is assigned to a dedicated data science team. When the pipelines feeding the analysis turn out to be the constraint, we plan for that at scoping.

Every R specialist we assign works remotely inside your tools as a dedicated member of your team, with the management on our side. It is how companies hire remote developers without opening an offshore office of their own.