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Complex day at Headway

Commit the new ranker before enrollment locks in weak matches

You’re the ai / ml engineer. Your team is in the room. Printed Oct 19, 2026.

The enrollment ranker improves booking while early signs question whether those matches hold.

Fast access for patients pulls against evidence that the provider relationship will continue beyond a first visit.

Who you’d be doing this for

“I finally got an appointment, then the therapist said my situation needed a different kind of care.”

Soren Lindqvist · Benefits-eligible patient

She used her employer benefit to find an in-network therapist and booked from the ranked search results.

What is at stake

First-appointment bookings rose, yet more early matches appear to end after one visit. You must weigh faster access against incomplete evidence that patients are reaching the right clinician.

Why it isn’t already fixed

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

  • first-visit conversion vs sustained care
  • release timing vs outcome evidence
  • patient access vs clinical fit
  • model gains vs operational reversibility

Why Headway

Search and matching determine whether insured patients reach an in-network clinician who can support ongoing outpatient care.

Written with these in mind

Applied ML engineerRanking and relevance specialistHealthcare ML practitioner

Not your kind of problem? 75 more at Headway, 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.