Search Fields Object for Job🔗︎
Job Title and Profession🔗︎
JobTitle 🔗︎ string
jobtitle🔗︎
Search for jobs by their job title. Example query: jobtitle:"software engineer"
ProfessionCode 🔗︎ integer
professioncode🔗︎
Search for jobs by their job title normalized to Textkernel Profession codes. Example query: profession_code:11
ProfessionClass 🔗︎ integer
professionclass🔗︎
Search for jobs by their job title normalized to Textkernel Profession Class codes. Example query: profession_class:19
ProfessionOnet2019 🔗︎ string
professiononet2019🔗︎
Search for jobs by their job title normalized to O*NET 2019 occupation codes. Example query: profession_onet2019:"15-1252.00"
ProfessionIsco2008 🔗︎ string
professionisco2008🔗︎
Search for jobs by their job title normalized to ISCO-08 occupation codes. Example query: profession_isco2008:"2512"
ProfessionKldb2020 🔗︎ string
professionkldb2020🔗︎
Search for jobs by their job title normalized to KldB 2020 occupation codes (German classification). Example query: profession_kldb2020:"43302"
ProfessionUkSoc2010 🔗︎ string
professionuksoc2010🔗︎
Search for jobs by their job title normalized to UK SOC 2010 occupation codes. Example query: profession_uk_soc2010:"2136"
Workfield 🔗︎ object
workfield🔗︎
Search for jobs by their work field, based on the job title normalized to Textkernel Profession Group codes. Furthermore, it is possible to filter by the required experience level. Experience levels are normalized to the Textkernel Experience Level codes.
This field includes the following sub-fields:
- profession_group (type int): the work field of the job;
- experience_level (type int): the required experience level.
Example query: workfield:{profession_group:223 experience_level:3}
Location🔗︎
Location 🔗︎ string[]
location🔗︎
Search for jobs by their location. It is possible to search by city or postal code. For a more precise location search, add the ISO country code before the city name or postal code. When searching by city name in the US, it is recommended to add the ISO state code after the city name. Example queries: location:"New York", location:"US New York", location:"US New York NY", location:"10001", location:"US 10001"
Region 🔗︎ string
region🔗︎
Search for jobs by ISO 3166-2 region codes. Some exceptions to the subdivisions used by this field:
- United States: this field contains US state codes, see ISO 3166-2:US.
- France: this field contains the "département" and not the French administrative unit called "région" in France. It also includes the French overseas departments and the overseas territories as regions of France. See ISO 3166-2:FR.
- United Kingdom of Great Britain and Northern Ireland: the regions are England GB-ENG, Scotland GB-SCT, Ireland GB-NIR and Wales GB-WLS. Use the subregion field for a more specific level. See ISO 3166-2:GB.
Example queries: region:"US-AL", region:"FR-16"
Subregion 🔗︎ string
subregion🔗︎
Search for jobs by ISO 3166-2 sub-region codes. For the United States, this field is not populated. Example queries: subregion:"GB-MAN", subregion:"FR-67"
Country 🔗︎ string
country🔗︎
Search for jobs by ISO 3166-2 country codes. Example query: country:"US"
LocationRemotePosition 🔗︎ string
locationremoteposition🔗︎
Search for jobs by their remote work indicator. Example query: location_remote_position:"yes"
Organization🔗︎
OrgName 🔗︎ string
orgname🔗︎
Search for jobs by the name of the hiring organization. Example query: org_name:"Acme"
OrgNormalizedName 🔗︎ string
orgnormalizedname🔗︎
Search for jobs by the normalized name of the hiring organization. Example query: org_normalized_name:"Acme"
OrgIndustry 🔗︎ string
orgindustry🔗︎
Search for jobs by the industry of the hiring organization. Example query: org_industry:"Software"
OrgContactPerson 🔗︎ string[]
orgcontactperson🔗︎
Search for jobs by the contact person at the hiring organization. Example query: org_contact_person:"Jane Smith"
OrgPhone 🔗︎ string[]
orgphone🔗︎
Search for jobs by the phone number of the hiring organization. Example query: org_phone:"+17173856138"
OrgEmail 🔗︎ string[]
orgemail🔗︎
Search for jobs by the email address of the hiring organization. Example query: org_email:"jobs@acme.com"
OrgWebsite 🔗︎ string[]
orgwebsite🔗︎
While it is possible to search for jobs using the organization website URL, this field is mainly intended to display that information in the results. Example query: org_website:"https://acme.com"
OrgAdvertiserType 🔗︎ string
orgadvertisertype🔗︎
Search for jobs by the advertiser type of the hiring organization (e.g. direct employer vs. staffing agency). Example query: org_advertiser_type:"direct"
Requirements🔗︎
ExperienceYears 🔗︎ object
experienceyears🔗︎
Search for jobs by required years of experience. This field supports the following sub-fields:
- minimum (type numeric): the minimum years of experience required;
- maximum (type numeric): the maximum years of experience required.
Example queries: experience_years.minimum:<=5, experience_years:{minimum:>=2 maximum:<=10}
EducationLevelLocal 🔗︎ string
educationlevellocal🔗︎
Search for jobs by required education level normalized to Textkernel Local Education Level codes. Example query: educationlevel_local:"US_7"
EducationLevelInternational 🔗︎ string
educationlevelinternational🔗︎
Search for jobs by required education level normalized to Textkernel International Education Level codes. Example query: educationlevel_international:3
LanguageSkills 🔗︎ string[]
languageskills🔗︎
Search for jobs by required language skills, normalized to the Textkernel Skills Taxonomy codes. Example query: language_skills:"KS123K75YYK8VGH90NCS"
ItSkills 🔗︎ string[]
itskills🔗︎
Search for jobs by required IT skills, normalized to the Textkernel Skills Taxonomy codes. Example query: it_skills:"KS1200H6XYN1CR0G5NZ0"
ProfessionalSkills 🔗︎ string[]
professionalskills🔗︎
Search for jobs by required professional skills, normalized to the Textkernel Skills Taxonomy codes. Example query: professional_skills:"KS1212B6QR5SK1LSD4S4"
SoftSkills 🔗︎ string[]
softskills🔗︎
Search for jobs by required soft skills, normalized to the Textkernel Skills Taxonomy codes. Example query: soft_skills:"KSLSQ90KU2MTW9EUR1B5"
DriverLicenses 🔗︎ string[]
driverlicenses🔗︎
Search for jobs by required driver's licenses. Example query: drivers_licenses:"B"
Job Conditions🔗︎
EmploymentTypeCode 🔗︎ string
employmenttypecode🔗︎
Search for jobs by employment type (e.g. full-time, part-time). Values are normalized to Textkernel Employment Type codes. Example query: employment_type_code:"full_time"
ContractTypeCode 🔗︎ string
contracttypecode🔗︎
Search for jobs by contract type (e.g. permanent, temporary). Values are normalized to Textkernel Contract Type codes. Example query: contract_type_code:"permanent"
WorkingHours 🔗︎ string
workinghours🔗︎
Search for jobs by their working hours indicator. Example query: working_hours:"full_time"
WorkingHoursPerWeek 🔗︎ object
workinghoursperweek🔗︎
Search for jobs by required working hours per week. This field supports the following sub-fields:
- minimum (type numeric): the minimum number of hours per week;
- maximum (type numeric): the maximum number of hours per week.
Example queries: working_hours_per_week.minimum:>=32, working_hours_per_week:{minimum:>=24 maximum:<=40}
SalaryMinimum 🔗︎ numeric
salaryminimum🔗︎
Search for jobs by minimum salary. Example query: salary_minimum:>=50000
SalaryMaximum 🔗︎ numeric
salarymaximum🔗︎
Search for jobs by maximum salary. Example query: salary_maximum:<=100000
StartDate 🔗︎ string
startdate🔗︎
Search for jobs by their start date, in the format YYYY-MM-DD. Example query: start_date:>=2025-01-01
ApplyBefore 🔗︎ string
applybefore🔗︎
Search for jobs by their application deadline, in the format YYYY-MM-DD. Example query: apply_before:>=2025-06-01
NumberOfOpenings 🔗︎ integer
numberofopenings🔗︎
Search for jobs by the number of available openings. Example query: number_of_openings:>=2
Job Content🔗︎
VacancyText 🔗︎ string
vacancytext🔗︎
Search for jobs by their full vacancy text. Example query: vacancy_text:"agile development"
JobDescription 🔗︎ string
jobdescription🔗︎
Search for jobs by the job description section of the vacancy. Example query: job_description:"Python"
CandidateDescription 🔗︎ string
candidatedescription🔗︎
Search for jobs by the candidate profile section of the vacancy. Example query: candidate_description:"team player"
EmployerDescription 🔗︎ string
employerdescription🔗︎
Search for jobs by the employer description section of the vacancy. Example query: employer_description:"scale-up"
ConditionsDescription 🔗︎ string
conditionsdescription🔗︎
Search for jobs by the conditions description section of the vacancy. Example query: conditions_description:"pension"
ApplicationDescription 🔗︎ string
applicationdescription🔗︎
Search for jobs by the application instructions section of the vacancy. Example query: application_description:"cover letter"
ReferenceNumber 🔗︎ string
referencenumber🔗︎
Search for jobs by their reference number. Example query: reference_number:"REQ-2025-001"
VacancyUrl 🔗︎ string
vacancyurl🔗︎
While it is possible to search for jobs using their vacancy URL, this field is mainly intended to display that information in the results. Example query: vacancy_url:"https://acme.com/jobs/123"
PostDate 🔗︎ string
postdate🔗︎
Search for jobs by the date they were posted, in the format YYYY-MM-DD. Example query: post_date:>=2025-01-01
PriorityJob 🔗︎ string
priorityjob🔗︎
Search for jobs by their priority flag. Example query: priority_job:"true"
AgenciesNotWanted 🔗︎ string
agenciesnotwanted🔗︎
Search for jobs by their agencies-not-wanted flag. Example query: agencies_not_wanted:"true"
IsEmployerAnonymous 🔗︎ string
isemployeranonymous🔗︎
Search for jobs where the employer is listed anonymously. Example query: is_employer_anonymous:"true"
System Fields🔗︎
DocumentDate 🔗︎ string
documentdate🔗︎
Search for jobs by the last modification date of the job record, in the format YYYY-MM-DD.
Example queries: documentdate:2025-06-01, documentdate:>=2025-01-01
Owner 🔗︎ string
owner🔗︎
Search for jobs by their owner (the user who created or is responsible for the job record). Example query: owner:"john.doe@acme.com"
Comments 🔗︎ object[]
comments🔗︎
Search for jobs by their comments. This field includes the following sub-fields:
- note (type string): the text of the comment;
- date_added (type date): the date the comment was added;
- author (type string): the author of the comment;
- action (type string): the action associated with the comment.
Example queries: comments: { note:"urgent" }, comments: { author:"jane.doe@acme.com" date_added:>=2025-01-01 }