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Fix scoring of leads that sound related but need another trade

You’re the ai / ml engineer. Your team is in the room. Printed Oct 21, 2026.

The lead scorer is rewarding language that looks relevant but does not describe work a pro performs.

Fewer mismatched paid leads protects pro budgets, while preserving enough eligible matches protects homeowner choice.

Who you’d be doing this for

“I opened three leads this week that sounded electrical, then they were jobs my crew does not do.”

Rania Nasr · Electrical Business Owner

Runs a small residential electrical business and pays for homeowner leads in the services her crews can perform.

What is at stake

Eight percent of paid leads in affected categories are later marked Not what I do. You have to weigh tighter relevance against the matches homeowners and pros still need.

Why it isn’t already fixed

Every obvious fix costs something else. That’s the part you’d have to decide.

  • lead relevance vs. accepted lead volume
  • feature precision vs. serving latency
  • automated labels vs. reviewed evidence
  • category controls vs. model generalization

Why Thumbtack

Paid leads and pro targeting sit at the center of how local service businesses decide whether to keep buying homeowner projects.

Written with these in mind

production-minded ML engineermarketplace applied scientistML systems builder

Not your kind of problem? 72 more at Thumbtack, or browse every organization.

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.