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Skills application

Skills application
Complete

In this skills application, you will extract business and technical requirements from stakeholder profiles and scenario information. Your task is to translate those needs into a clear ML problem scope, document constraints and define success metrics - as you would in a real scoping session.

Skills application illustration

Context

You are on the data team at StreamStyle, a mid-sized e-commerce company focused on on-demand fashion rentals. Retention has dipped over the last two quarters. Leadership wants to explore how ML could improve retention. Review input from theCFO,head of marketing andsenior data engineer (see stakeholder document in your Multiverse materials) and synthesise a structured requirements view for a potential ML initiative.

Success criteria

A strong submission will:

  • Clearly articulate an ML problem scope aligned with a business objective.
  • Identify key data requirements implied or stated in the scenario.
  • Highlight constraints and dependencies (budget, infrastructure, regulation).
  • Specify success metrics that reflect stakeholder priorities and expected impact.

Submitting unlocks the solution example on the next page.

Exercise: Stakeholder profiles

Download Unit 2 - Skills application - Stakeholder profiles (same PDF as on My Multiverse).

Download stakeholder profiles (PDF)

Upload completed work (Coming Soon)

Reflect

Review each profile's goals, concerns and constraints before you complete the form.

What is the ML problem scope?

What are the key data requirements?

Describe the constraints and dependencies.

What success metrics did you define?

After you submit

Reflect on how you balanced business and technical concerns, what trade-offs you made between stakeholders and how this process might differ in another industry.

What is the ML problem scope?
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What are the key data requirements?
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Describe the constraints and dependencies.
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What were the success metrics you defined?
0 words
In progress