People & HR · Talent Acquisition

Samso Managed Services · Last Updated · Apr 2026

Resume Screening & Shortlists

Inbound resumes scored against your rubric, screened through the four checks that matter, and shortlisted with written rationale for every advance - so the hiring loop walks in with 8 strong candidates, not 247 unread PDFs.

What the managed workflow does

Reads every resume

ATS extraction + parser pulls structured data from every resume - title, tenure, stack, narrative - so the rubric can score apples-to-apples regardless of format.

Scores against your rubric

Required skills, level expectations, culture-add signals - graded against your bar, not a generic library. Each candidate gets a numeric score and a written rationale.

Routes by verdict

Pass goes straight to the hiring loop. Maybe is queued for trial task or recruiter callback. Reject is auto-declined with a logged reason - no candidates get ghosted.

Surfaces drift

Per-rule pass rates, source ROI, and rep-vs-team calibration tracked over time - so the rubric tightens with the hiring data, not against it.

Funnel · 247 in → 8 shortlisted with rationale · loop-ready

247 RESUMES · 4 RULES · 8 SHORTLIST · 3.2% PASS RATE

Pass?Maybe×Reject
INBOUND · 30D247RESUMES · APRSr Eng · 4 reqs · 3 sourcesapplied · referred · sourcedSCREENING FUNNEL8 SHORTLIST3.2% pass rate247 INRUBRIC RULES · APPLIED1ATS · keyword + stack142 pass · 57%2Recruiter screen · phone64 pass · 26%3Rubric scoring · LLM21 pass · 9%4Hiring mgr triage8 pass · 3%SHORTLIST · 6 OF 8 · LOOP-READYARAnika R.Sr Eng · StripePASS5y ICN+payments · OSS contributor · stack matchRUBRIC SCORE92DMDevon M.Staff · LinearPASSOwned billing rewrite · prior Stripe alum · ref strongRUBRIC SCORE88PKPriya K.Eng · PlaidPASSBank-data depth · clear writing · scoping example realRUBRIC SCORE86SOSam O.Sr · NotionMAYBEGeneralist · less payments depth · culture-add strongRUBRIC SCORE78JMJordan M.Sr · AsanaMAYBEStrong system design · coachable on domain · 7y expRUBRIC SCORE74RARiya A.Eng · BrexMAYBEB2B fintech context · GitHub light · trial task pendingRUBRIC SCORE714 rules applied · written rationale per candidate · ready for the hiring panel · drift caught at recruiter screen

Inputs scored

Resume + cover · ATS-extractedJob spec + leveling rubricPast hires · what workedRecruiter screen · phone notes

What lands per req

Shortlist · loop-ready candidatesMaybe queue · revisit + trial taskReject · auto-decline + logWritten rationale per candidate

Inputs scored

  • Resume + cover. ATS-extracted resume + cover letter parsed into structured fields - title, tenure, stack, narrative - for apples-to-apples scoring.

  • Job spec + rubric. Role expectations, required skills, level signals, and culture-add criteria - graded against your bar, calibrated quarterly.

  • Past hires · what worked. Prior hires' resumes weighted by tenure + perf signal so the rubric learns which patterns predict success in your context.

  • Recruiter phone notes. 30-min phone screen notes feed score updates with motivation, comp, and timing signal recruiters surface in conversation.

What lands per req

  • Shortlist with rationale. 8-candidate loop-ready stack with rubric score, written rationale, and red-flag callouts where they apply.

  • Maybe queue. Borderline candidates queued for trial task or recruiter callback - not lost in the noise, not advanced without evidence.

  • Auto-decline log. Reject path with a logged rationale and a same-day decline note - no candidate gets ghosted.

  • Hygiene + calibration metrics. Per-rule pass rates, source ROI, panel-vs-rubric calibration - the rubric tightens with the hiring data.

What you get, every week

A loop walking in calibrated

Hiring panels get 8 strong candidates with written rationale - not 30 maybe-look-at-them PDFs and a recruiter rant about volume.

A faster cycle

Median time-to-shortlist drops from 9 days to under 3. Top-of-funnel volume stops dictating recruiter capacity.

An auditable funnel

Every advance and decline is rationaled, sourced, and dated - bias audits and EEO compliance are reading, not reassembly.

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