How to Filter and Search Your Candidate Database

You can filter a candidate database quickly if three things are true: the fields you filter on are filled in, the values are spelled the same way, and you have a way to save the search you repeat. The filters themselves are the easy part.

This guide covers what to clean up first, which filters and search operators are worth using, and how to reuse a search. It uses TalentsGrid as the example tool. TalentsGrid is an AI hiring copilot for freelance recruiters and small teams: it scores each CV against your job with quotes as evidence, turns gaps into interview questions, and keeps your candidate data yours.

Key takeaways

• Filters only work on clean data. Fix locations, experience and skills before you build any search.
• Combine a text search (with AND, OR, NOT) with range filters for experience and salary.
• Save the searches you repeat so you do not rebuild them every week.
• For a ranked shortlist against one job, scoring CVs beats filtering. Filters narrow the pool, scoring orders it.

Why does searching a candidate list get slow?

Searching gets slow when the list stops being scannable and the data is inconsistent. Say you have 180 candidates and a hiring manager asks for “a frontend developer in Hanoi with at least 3 years of experience.” In a spreadsheet you Ctrl+F for “Hanoi”, miss the rows typed “Ha Noi”, open a few profiles to check experience, and end up calling whoever applied most recently.

The fix is not a faster scroll. It is turning that sentence into conditions the tool can apply: a location, a minimum experience, a skill.

What should you clean up before you filter?

Clean the four fields you filter on most: location, years of experience, skills and CV. A filter cannot match what is typed three different ways.

1. Location. Pick one spelling per city. “HCMC”, “Ho Chi Minh” and “Saigon” are three values to a filter. TalentsGrid location filters match on text, so a consistent spelling matters.
2. Years of experience. Fill it in when you add the candidate. Range filters skip candidates with no value.
3. Skills. Choose one name per skill (“React”, not “ReactJS” and “React.js”). The skills field on a candidate lets you pick from a list or type your own and press Enter.
4. CV. Upload it when you add the candidate. “Later” tends to mean never.

This is one-time work. After it, every filter below gets more reliable.

Which candidate filters does TalentsGrid have?

The candidates page has a search box, three quick toggles and a filter panel. Each one narrows the list, and you can combine them.

Filter	Where	What it does
Search box	Top of the page	Searches name, email, skills and current position. Supports AND, OR, NOT and brackets.
My candidates	Quick toggle	Shows only candidates you own.
Has CV	Quick toggle	Shows only candidates with a CV uploaded.
Favorites	Quick toggle	Shows only candidates you starred.
Location	Filter panel	Pick one or more locations from the ones in your database.
Current company	Filter panel	Pick one or more companies.
Experience (years)	Filter panel	Minimum and maximum years.
Current salary	Filter panel	Minimum and maximum, read from the candidate’s current salary field.
Level	Filter panel	Lead, Senior, Middle, Junior or Fresher.
Tags	Filter panel	Tags written as key:value, for example skill:react.

Every active filter shows as a pill under the search row, and you can remove pills one at a time or clear all of them. The filters are also written into the page address, so you can bookmark a filtered list.

How do you use boolean search on candidates?

Type operators into the search box. The info icon next to it lists them: AND needs both terms, OR needs either, NOT excludes a term, and brackets group conditions. The built-in example is React AND (Node OR Vue).

A few patterns that work well:

• React AND (Node OR Vue) finds React developers who also list Node or Vue.
• Python NOT intern removes anyone with “intern” in their skills or current position.
• QA AND (automation OR Selenium) narrows a broad QA pool.

Text search matches the words inside a candidate’s name, email, skills and current position, so it finds a skill only if it is written on the profile. This is why the skills cleanup above pays off.

How do you filter for a typical request?

Turn the request into conditions, then apply them in order from broadest to narrowest. For “frontend developer in Hanoi, 3+ years, budget under 25 million VND”:

1. Open the candidates page.
2. Search React OR Vue OR JavaScript.
3. Open the filter panel and pick Hanoi under Location.
4. Set Experience minimum to 3.
5. Set Current salary maximum to 25000000.
6. Switch on Has CV if you plan to read CVs before calling.

Check the pills to confirm what is active, then open the profiles that remain. The length of the result depends on your data. The point is that you open a handful of profiles instead of all of them.

Salary comparison reads the number in the candidate’s current salary field, so keep that field to plain numbers in one currency. If half your candidates are in USD and half in VND, filter in separate passes.

Can you save a search you repeat?

Yes. Saved views store a filter combination under a name, and you apply it again from the Saved views menu. Click Save current view, give it a name such as ”.NET seniors 2026”, and it appears under “My saved views”. You can delete a view from the same menu.

Save the three or four searches you run every week, like “Senior frontend, Hanoi” or “Has CV, my candidates”. A saved view keeps the search text, skills text and filters together.

Can the copilot build a shortlist for you?

Yes, for a specific job. Instead of filtering by hand, you can ask the chat to evaluate candidates against a job’s criteria, compare two to five candidates side by side, and shortlist the top matches. The chat offers these as suggestions, such as “Shortlist the top matches” and “Export matches to CSV”.

The difference from filters is what you get back. A filter returns everyone who matches a condition. Scoring reads each CV against the job’s requirements, shows a quote from the CV for each one, and ranks the candidates. Scoring one CV against a job takes about 1.5 seconds. You can read more on the CV scoring page.

The copilot recommends. It does not accept or reject anyone. When you start a shortlist from a candidate card, you see a preview and click to confirm, and writes made from chat wait for your approval. Most AI tasks cost one credit; see pricing for monthly credits per plan.

A workable routine is to filter first to get a relevant pool, then score that pool against the job.

What about spreadsheets?

A spreadsheet is fine for a small list. Filter views in Google Sheets handle simple conditions. Where they struggle is multi-select (Hanoi or Ho Chi Minh City), numeric ranges on text columns, and keeping each CV linked to its row. If you manage a few dozen candidates, a sheet works. Beyond that, a tool that stores the CV with the profile saves you the manual linking.

If you do move from a sheet, TalentsGrid imports candidates from spreadsheets and exports the filtered list to Excel. Your data stays yours. For why that matters, see why candidate data should not be hostage.

What filtering cannot do yet

Be realistic about the gaps:

• There is no filter for “interviewed but not hired” on the candidates page. Interview stages live in the pipeline view.
• Location and company filters match on text, so inconsistent spellings split your results.
• Salary and experience filters depend on the fields being filled in as numbers.

Once your shortlist is moving to interviews, the next lever is note quality. See interview notes most startups get wrong.

FAQ

What is the fastest way to find the right candidate in a large database?

Clean the key fields first, then combine a boolean text search with range filters for experience and salary. Save the combination as a view. For a ranked list against one job, score the filtered pool rather than reading every profile.

Does TalentsGrid support boolean search for candidates?

Yes. The candidate search box accepts AND, OR, NOT and brackets, for example React AND (Node OR Vue). It searches name, email, skills and current position. An info icon next to the box lists the operators.

Can I save a candidate search in TalentsGrid?

Yes. Use Save current view on the candidates page, give the view a name, and apply it later from the Saved views menu. A saved view keeps your search text and filters. You can delete views you no longer need.

Can AI shortlist candidates without my approval?

No. The copilot recommends and ranks, and you decide. Shortlisting, rejecting and other writes show a preview that you confirm. The copilot never accepts or rejects a candidate on its own.

Which filters does the candidate list include?

Search, My candidates, Has CV and Favorites toggles, plus location, current company, experience range, salary range, level and tags in the filter panel. Active filters appear as removable pills.

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