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Design

Design Hybrid Search for an E-Commerce Product Catalog

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

Design Hybrid Search for an E-Commerce Product Catalog. Advanced challenge in design. Designing real products under real constraints, earn a blockchain-verif...

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Design and prototype a hybrid (BM25 + dense vector) search that lifts nDCG@10 by at least 12% over BM25 on the retailer's 90-day search logs.

This is not a design exercise. It is the work a product designer does between a brief and a shipped interface. That distinction matters to every hiring manager who has seen candidates redesign Spotify's homepage and none who have worked under real product constraints.

When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."

Earning criteria — what you'll demonstrate

  • Combine lexical and dense retrieval into a single ranked list
  • Apply multilingual embedding models to a real polyglot catalog
  • Evaluate ranking quality with nDCG@k on click-derived labels
  • Communicate an architecture trade-off (latency, cost, freshness) to non-search engineers

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Aligned coursework coming soon.

Careers

Career paths this challenge builds toward

Completing this challenge demonstrates skills that transfer directly to these roles:

AI Solutions Architect

Designing a hybrid retrieval architecture that survives multi-language, multi-tenant, and freshness constraints is the bread-and-butter deliverable of an AI solutions architect at any commerce company.

This challenge sharpens

  • hybrid-search
  • reciprocal-rank-fusion
  • multilingual-retrieval

Machine Learning Engineer

Operating BM25 + dense retrieval as a measured ranking system maps directly onto how MLEs ship search and ads ranking.

This challenge sharpens

  • bm25
  • embedding-models
  • evaluation

Data Scientist

Building click-derived labels and reporting nDCG@k by slice is the kind of measurement work data scientists own in search and recommendation teams.

This challenge sharpens

  • evaluation
  • hybrid-search
  • multilingual-retrieval

One more thing

You can put a credential on your CV by Friday.