Define the interval precisely
Specify start and end boundaries and how missing subscription dates should be treated. Establish the fields the custom step expects.
Scientist · Custom code
Add specialist logic without losing the analytical path.
Extend research workflows with custom code where the question calls for it. Scientist’s existing offering includes Python, R and Java/Scala logic connected to the surrounding preparation and analysis.
Custom code
Define a research-specific subscription interval
Add a Python step that derives observation intervals from subscription dates for the renewal study.
Workflow input
Subscription dates and account identifiers
Custom logic
Python · Derive observation interval fields
Review output
Inspect interval boundaries and missing-date handling
Keep specialized code attached to its analytical inputs and outputs.
Follow the investigation
A concrete path through the research.
A renewal study may need a domain-specific observation interval that does not match a standard date transformation. The code step should expose its assumptions through clear inputs, outputs and representative cases.
Connect the implementation
Add the transformation in a supported language and environment. Place it between subscription preparation and the analytical steps that use the derived interval.
Test the difficult cases
Inspect ordinary dates, boundary dates and incomplete records. Review whether the generated interval fields match the study definition before continuing.
What to examine
Put the analytical choices in view.
The useful output is not just a completed run. It is an analysis whose inputs, assumptions and limits another researcher can question.
Input/output contract
Required fields, resulting types and the handling of invalid inputs.
Method review
The business definition expressed by the code—not only whether it executes.
Downstream effect
How derived intervals influence eligibility, grouping or evaluation.
Scientist in the DO Stack
Take the research to the right next owner.
Developer supports the engineering review when specialist research code needs to become maintained software. Bring the method definition and test cases into that discussion; agree the artifact transfer and deployment requirements separately.
What should we validate for implementation?
Confirm supported language versions, packages, resource limits and execution isolation. The language framing does not imply unrestricted dependency installation, sandbox guarantees or identical behavior in every deployment.
What should the team bring to a first discussion?
Bring one research question, its source requirements, a relevant workflow and the review criteria. Confirm available capabilities, access and operating requirements before using sensitive material or applying a finding operationally.
Start with a question worth investigating.
Bring the question, the available data and the people who understand it. We’ll work through the analytical path, the review points and the implementation requirements.