Data Science Delivery Pack
Skill: delivering-data-science
Record details
| ID | Field | Project value |
|---|---|---|
artifact_id |
Artifact ID | |
project |
Project | |
skill |
Skill | |
version |
Version | |
date |
Date | |
status |
Status | |
author |
Author | |
owner |
Owner | |
approver |
Approver | |
purpose |
Purpose | |
business_outcome |
Business outcome | |
scope |
Scope and exclusions | |
source_inputs |
Inputs and sources | |
assumptions |
Assumptions and constraints | |
decisions |
Decisions | |
rationale |
Rationale | |
risks |
Risks | |
exceptions |
Exceptions | |
open_items |
Open items | |
due_date |
Due date | |
acceptance_criteria |
Acceptance criteria | |
evidence_location |
Evidence location | |
reviewer_decision |
Reviewer decision | |
next_gate |
Next stage gate |
Domain analysis and decisions
Business hypothesis and decision boundary (hypothesis)
Define the hypothesis, baseline, success criteria, and decisions not delegated to automation.
Enter project evidence, conclusion, and owner.
Data features and labels (data_features)
Fix prediction time, data purpose, feature availability, label delay, and leakage checks.
Enter project evidence, conclusion, and owner.
Experiment and evaluation protocol (evaluation)
Set temporal split, independent test, group errors, costs, and comparator metrics.
Enter project evidence, conclusion, and owner.
Reproducibility evidence (reproducibility)
Record data version, code, environment, randomness, and evaluation artifacts.
Enter project evidence, conclusion, and owner.
Model card and limitations (model_card)
State intended use, performance, known failures, affected groups, and human fallback.
Enter project evidence, conclusion, and owner.
Production service and rollout (production)
Define shadow or canary gates, human process, observability, and release approval.
Enter project evidence, conclusion, and owner.
Monitoring retraining and change (monitoring)
Set drift, effectiveness, bias, retraining triggers, and independent review.
Enter project evidence, conclusion, and owner.
Rollback and retirement (rollback)
Define stop thresholds, rollback, data retention, and retirement ownership.
Enter project evidence, conclusion, and owner.
Working registers
Data Features (features)
Record feature sources, availability, and use constraints.
Feature (feature) |
Definition (definition) |
Source (source) |
Rule (rule) |
Owner (owner) |
Evidence (evidence) |
|---|---|---|---|---|---|
Validation Monitoring (validation)
Track independent validation, drift, and stop actions.
Metric (metric) |
Validation (validation) |
Drift threshold (drift_threshold) |
Test result (test_result) |
Owner (owner) |
Evidence (evidence) |
Review date (review_date) |
|---|---|---|---|---|---|---|