How to Match Candidates to Jobs Using ATS Data with

Unified.to’s ATS API supports candidate-job matching by providing normalized access to open jobs, candidate profiles, applications, and documents across different applicant tracking systems, while emphasizing that matching is primarily a data-modeling challenge because field availability differs by provider. Teams can ingest job requirements and candidate information, connect candidates to jobs through applications, retrieve resumes when supported, and extract structured, semi-structured, and unstructured features such as experience, education, application answers, resume text, and job descriptions. Since skills fields, resume access, and outcome data like hires or rejections are inconsistently populated, matching systems should treat these signals as optional and gracefully handle missing data. Organizations can apply keyword matching, embeddings, rule-based approaches, or machine-learning models in their own systems, using historical application outcomes as labels only where reliable data exists. Incremental reads and supported webhooks can keep scores current as jobs, candidates, applications, and documents change, while Unified.to supplies the ingestion and relationship layer rather than prescribing scoring models, deduplication, or guarantees across ATS providers.

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