Data Scientist & Actuary
Compare model candidates and hand a reproducible result to the production team.
Prepare reviewable inputs for an AI-assisted workflow
Run the mortgage kit and inspect the income discrepancy. Define which source fields an assistant may use, which statements require evidence, and where a human must review its recommendation.
Start with the browser demo or download the local kit. For the workspace exercise, you need approved access to the relevant Genedata capabilities and a reviewer for your output.
Practice tasks
0 / 4 completed
Notes and progress are saved on this device.
Experiment with the context intact.
Compare model candidates and hand a reproducible result to the production team.
Select a versioned dataset and define the evaluation question, baseline, and decision criteria.
Track parameters, metrics, artifacts, and upstream data references with each experiment run. Log cost explicitly where required.
Compare candidates on quality and cost using consistent evaluation data. Record assumptions and limitations.
Register the chosen model version and hand its run reference and evaluation evidence to ML engineering and governance.
Expected handoff
A reproducible model candidate, evaluation record, and documented limitations.
Explore your platform capabilitiesMeasure your progress
- Time required to reproduce a candidate run
- Experiments with complete data and cost references
Use AI to help explore hypotheses and summarize results; retain statistical review and human approval of the conclusion.