Powered by the same core methods behind behind DataScava, TalentBrowser applies Automated Skills Analytics to mine and measure the raw textual content on resumes, profiles, and job descriptions.

It analyzes the full text of each resume or profile, generating weighted topic scores and other structured metadata about skills, roles, experience, location, education, and more.

This metadata can be used in Talent Matching, People Analytics, HR reporting, Business Intelligence . . .  and other initiatives — surfacing deterministic signals at scale across your entire candidate pool.

How It Works

Automated Skills Analytics is powered by DataScava’s deterministic stack:

  • DSIndex   |Domain-Specific Language Processing (DSLP)
  • DSTopics | Tailored Topics Taxonomies (TTT)
  • DSMatch  | Weighted Topic Scoring (WTS)

Unlike AI, LLMs, NLP, or semantic toolkits that “guess” at meaning, TalentBrowser uses Machine Training + Human Intelligence — an explainable, transparent, and user-controlled approach that mines and measures exactly what you care about.

 

A File Matches Datagrid with Skills Analytics

Data-Driven Decisions

Every time you receive an updated resume or profile, TalentBrowser re-indexes the file on the fly. Earlier versions and topic scores are automatically saved for reference.

If the candidate meets the thresholds for any open job, they are auto-assigned to the role and added to a Hot List for review. Time-sensitive workflows and standardized scoring all support more confident decision-making.

You can continuously refine your skills model over time — making your software smarter with every hire, and ensuring alignment across hiring managers, recruiters, and departments.

Precision Skills Measurement at Scale

Metadata generated at the file level flows into your dashboards, search results, and analytics — making it available in TalentBrowser or any integrated talent solution or workflow.

You gain insight into individual and corpus-wide skills by topic, taxonomy, and source — enabling automatic, ongoing candidate filtering— and a clear line of sight into what matters most.

Weighted Topic Scoring (WTS)

WTS combines multiple weighted topics into each search, returning documents that meet or exceed user-defined thresholds.

  • Left bar = required threshold
  • Right bar = file’s calculated score

This visual scoring framework delivers transparent, sortable relevance — no guessing, no black box.

Highlighter for Refinement and Review

TalentBrowser’s Highlighter tool supports TTT refinement by clearly showing which terms triggered which topic scores. All key terms are color-coded and highlighted in context, enabling fast topic debugging and refinement.

Combined with multi-sort, rank, and filtering, this makes search and scoring explainable and actionable at scale.

Encapsulate Business Intelligence

With TalentBrowser, your organization’s evolving knowledge becomes a customizable search engine — available at the earliest stage of every hiring or talent decision.

You gain insight into individual and corpus-wide skills by topic, taxonomy, and source — enabling automatic, ongoing candidate filtering with total transparency.

Discover how Automated Skills Analytics can deliver deterministic, structured insight at scale — without training data, manual labeling, or black-box algorithms.