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Machine Learning · ML-13

Predict employee exits and tenure

Explore workforce models that connect employment spells, tenure, employer context and prior career pathways.

  • Synthetic records
  • Longitudinal
  • Nairobi + Lagos
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Scope & purpose

Connected scope

Connect job starts, exits, employers and education to explore retention and turnover.

  • Employment
  • Business
  • Demographics
  • Education

Define the prediction date and horizon. Keep earlier inputs separate from later outcomes.

Possible uses

Prediction prototyping · Feature exploration · Temporal validation · Cohort comparison

Who it is for

Labour economists · workforce teams · ML engineers · universities

Preview type
Illustrative format preview
Shows example structure and fields. It is not a sample extracted from the paid release.
Commercial availability
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What you receive

SD delivery standard
Published cities
Nairobi + Lagos
Record scope
Resident-level
Structure
Longitudinal

Striped Donkey delivery package

  • data/Agreed extract and formats
  • documentation/Schema, fields and relationships
  • evidence/Agreed release checks and limits
  • examples/Agreed loading and join examples
  • LICENSEApplicable rights
  • MANIFESTRelease and file inventory
  • CHECKSUMSSHA-256 fingerprints
  • DELIVERY_NOTEScope and handoff record

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15 illustrative rows · 11 fields · CSV

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Fields and record structure

Listed features

Resident-level · Longitudinal

  • employment start / end
  • tenure length
  • employer context
  • employment spells
  • employer / work transitions
  • earnings context
  • business lifecycle

Study question

Evaluation design

Can prior career and employer histories predict whether an active employment spell ends within 12 months and estimate its remaining duration?

Freeze features at an active-spell snapshot; report exit probability and time-to-event performance. Distinguish recorded end dates from voluntary resignation labels.

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Evidence you can inspect

Source & limitations

Review release-specific methods and published checks. Preview rows show format and scope; they do not certify a dataset.

Supporting references
NairobiEvidenceSamples
LagosEvidenceSamples
MethodsGenerationReproduce

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Licence & delivery

Free preview

Use free samples under the public-use policy or their dataset-specific licence. Attribution is required for publication and research outputs.

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Purchased dataset

Your agreement defines the release, licensed organization, permitted uses and duration. Commercial model training, external applications and redistribution require explicit agreement.

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