qode.world
Artificial Intelligence • HR Tech • Recruitment
qode. world is a company that leverages artificial intelligence to revolutionize the recruiting process. Their platform allows users to find candidates by sourcing data from billions of data points worldwide and provides data-driven insights. Users can connect with candidates directly through the platform, conduct customized AI-led interviews, and get comprehensive assessments. The service also integrates easily with LinkedIn, enhancing the talent pool and facilitating direct communication with candidates listed there. Qode. world offers additional recruiting services to assist in hiring for niche or senior roles. They are praised for their effectiveness in streamlining the hiring process and delivering quick results.
Contract Data/ML Engineer – Scoring Reliability, Candidate Archetypes
Job not on LinkedIn
9 hours ago
qode.world
Artificial Intelligence • HR Tech • Recruitment
qode. world is a company that leverages artificial intelligence to revolutionize the recruiting process. Their platform allows users to find candidates by sourcing data from billions of data points worldwide and provides data-driven insights. Users can connect with candidates directly through the platform, conduct customized AI-led interviews, and get comprehensive assessments. The service also integrates easily with LinkedIn, enhancing the talent pool and facilitating direct communication with candidates listed there. Qode. world offers additional recruiting services to assist in hiring for niche or senior roles. They are praised for their effectiveness in streamlining the hiring process and delivering quick results.
📋 Description
• Own the end-to-end implementation of two analytics features in Qode’s multi-agent assessment stack: (1) bootstrap confidence intervals (CIs) for per-question scores to communicate stability/disagreement across evaluators, and (2) candidate archetype discovery via clustering to surface talent patterns beyond raw scores. You’ll ship data plumbing, models, integrations, and lightweight reporting. • Data foundations: ensure per-candidate, per-question, per-agent criterion scores are structured and queryable; add/modify tables and JSON schemas as needed. • Bootstrap CIs: implement agent-level resampling, compute CI-90/CI-95, derive stability labels (high/medium/low), and persist alongside normalized scores; batch backfill existing records. • Archetypes: build standardized candidate feature vectors (per-question and/or per-criterion), run clustering (K-means/GMM/hierarchical), evaluate (e.g., silhouette), and generate human-readable labels from centroids and summaries. • Integrations: expose CI fields and cluster IDs/labels via API and internal dashboards; add basic charts/UX to surface stability and “candidate type.” • Reliability & performance: write unit/integration tests, guardrails (min N agents), and ensure pipeline runtime stays within agreed budgets. • Docs & handoff: clear README/runbooks covering data contracts, thresholds, and ops.
🎯 Requirements
• 3-5 years of experience in a relevant role • Python (pandas, NumPy, scikit-learn), SQL, DB migrations (e.g., Postgres). • Statistical resampling (bootstrap), clustering, model selection/validation. • Data engineering for batch jobs/backfills; API integration. • Pragmatic product sense for labeling clusters and communicating uncertainty.
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