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Searching for Candidates

The Search page is your primary tool for finding candidates in Skillsheet. It combines natural language understanding, advanced filters, and semantic matching to surface the most relevant candidates for any role.

The search bar at the top of the Search page accepts natural language queries. Type what you are looking for the way you would describe it to a colleague:

  • “Frontend engineer with React and TypeScript, 3+ years, Bay Area”
  • “Product manager who has worked at a Series B startup”
  • “Data scientist with NLP experience in New York”

Skillsheet parses your query, identifies key criteria, and returns ranked results. You do not need to use special syntax or Boolean operators, though you can combine natural language with filters for more precision.

Search Filters

Below the search bar, you can apply structured filters to narrow your results:

  • Location — Filter by city, state, country, or remote status.
  • Skills — Select specific technical or professional skills from the autocomplete list.
  • Experience (years) — Set a minimum and maximum range for years of experience.
  • Job Title — Filter by current or past job titles.
  • Company — Search for candidates who have worked at specific companies.

Combining Filters

Filters stack with your natural language query. For example, you can type “machine learning engineer” in the search bar and then apply a Location filter for “London” and an Experience filter of “5-10 years.”

To clear all filters, click the Reset Filters button.

Understanding Search Results

Search results appear as candidate cards, each displaying:

  • Match score — A percentage indicating how well the candidate matches your query.
  • Name and headline — The candidate’s name and current title or summary.
  • Key skills — A list of top skills relevant to your search.
  • Location — The candidate’s current location.
  • Experience summary — A brief overview of their work history.

Results are sorted by match score by default. You can re-sort by experience, location proximity, or last active date using the sort dropdown.

Skillsheet uses semantic search technology, which means it understands the meaning behind your query rather than relying on exact keyword matches. This has practical benefits:

  • Searching for “backend developer” will also surface candidates who list “server-side engineer” or “API developer” in their profiles.
  • Searching for “people manager” will match candidates with titles like “engineering lead” or “team lead.”
  • Skill synonyms are handled automatically. A search for “ML” will match “machine learning.”

Semantic search helps you discover candidates you might otherwise miss with traditional keyword-based tools.

Viewing Candidate Profiles

Click on any candidate card to open their full profile. A candidate profile includes:

  • Skillsheet — An AI-generated summary of the candidate’s core competencies and strengths.
  • Interview Results — If the candidate has completed a Skillsheet interview, you will see scores, answers, and AI-generated assessments.
  • Resume Information — Parsed resume data including work history, education, certifications, and skills.
  • Contact Information — Email and phone number (may require enrichment).
  • Activity History — A log of all interactions you or your team have had with this candidate.

Saving Searches

If you run a search you want to revisit later:

  1. Run your search with the desired query and filters.
  2. Click the Save Search button in the top-right corner of the results area.
  3. Give your saved search a name (e.g., “Senior React Devs - Austin”).
  4. Access saved searches from the Saved Searches dropdown on the Search page.

Saved searches preserve both your natural language query and all applied filters.

Contacting Candidates from Search Results

You can reach out to candidates without leaving the search results:

  1. Hover over a candidate card and click the Email icon.
  2. A compose window opens pre-filled with the candidate’s email address.
  3. Write your message or select an email template.
  4. Click Send.

You can also select multiple candidates using the checkboxes and click Bulk Email to message them all at once.

Enriching Candidate Data

Some candidate profiles may not have complete contact information. To enrich a candidate’s data:

  1. Open the candidate’s profile.
  2. Click the Enrich button next to the contact information section.
  3. Skillsheet will look up the candidate’s email address and phone number.

Each enrichment costs 1 credit. Enriched data is stored on the candidate’s profile and does not need to be looked up again.

Bulk Enrichment

To enrich multiple candidates at once:

  1. Select candidates from search results using the checkboxes.
  2. Click Bulk Actions > Enrich Selected.
  3. Confirm the credit cost and proceed.

Tips for Better Searches

  • Be specific. “Senior fullstack engineer with Python and React, 5+ years, fintech background” will yield better results than “developer.”
  • Use filters alongside natural language. Let the AI handle nuance while filters enforce hard requirements.
  • Try different phrasings. Semantic search is powerful, but varying your wording can surface different candidate pools.
  • Save frequently used searches. This saves time and ensures consistency across your sourcing workflow.