PredictLeads: Discover Job Openings

Find job openings by profession (O*NET occupation code) and company location, for example Sales Engineers.

Tool ID: predictleads_discover_job_openings

Run this action

Use the TypeScript SDK for one call. Use ctx.tools.execute(...) inside a Play for durable calls, scheduled calls, or CSV processing.

import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'predictleads_discover_job_openings',
  {
    "onet_codes": "example",
    "location": "example",
    "page": 1
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute predictleads_discover_job_openings --input '{
  "onet_codes": "example",
  "location": "example",
  "page": 1
}' --json

Example response

The static output schema lacks the details for a reliable example. Use deepline describe predictleads_discover_job_openings --json for the complete live contract.

Input reference

Returns a list of Job Openings filtered by a given profession (e.g. “Sales Engineers” or “Marketing Managers”) using O*NET occupation codes and/or location of the company. Note: This endpoint returns an estimated count of all results.

Name	Type	Required	Default	Details
`payload.onet_codes`	`string`	No	—	Comma-separated O*NET codes to filter by, such as “17-2071.00” for “Electrical Engineers” or “15-1254.00” for “Web Developers”. For full list of possible codes see: https://www.onetonline.org/find/all
`payload.location`	`string`	No	—	The response will include only companies located in the given country name or state name/abbreviation.
`payload.page`	`integer`	No	`1`	Page number of shown items. NOTE: If the parameter is not provided, the meta property `count` will be omitted from response for performance reasons. Minimum: 1.
`payload.limit`	`integer`	No	`30`	Limit the number of shown items per page. Maximum: 1000.

Output reference

Standard tool result payload.

Name	Type	Required	Default	Details
`result.data`	`object`	Yes	—	PredictLeads has historical jobs data since 2018 that includes over 220 million records, and is available for 2 million companies, which includes an average of 8.5 million active jobs at any given time. Job Openings are sourced directly from company websites which includes their career subpages, and ATS integrations. All Jobs are categorized using industry-standard O*NET codes . The Job Openings Dataset includes fields such as Job Opening Title, Job Opening URL, First Seen At, Last Seen At, See the live schema for the complete constraint.
`result.data.data`	`array`	Yes	—	—
`result.data.data[].id`	`string`	Yes	—	ID of the `JobOpening` object. Format: `uuid`.
`result.data.data[].type`	`"job_opening"`	Yes	—	Type of the `JobOpening` object.
`result.data.data[].attributes`	`object`	Yes	—	Attributes of the `JobOpening` object.
`result.data.data[].attributes.title`	`string`	Yes	—	Job title.
`result.data.data[].attributes.translated_title`	`string \| null`	Yes	—	Job title translated to English when a non-English language is detected.
`result.data.data[].attributes.normalized_title`	`string \| null`	Yes	—	Normalized job title with various noise (location, noise, team, gender, contract type etc.) information stripped.
`result.data.data[].attributes.description`	`string \| null`	Yes	—	`JobOpening` description.
`result.data.data[].attributes.url`	`string`	Yes	—	URL of the web page where the data was found. Format: `uri`.
`result.data.data[].attributes.first_seen_at`	`string`	Yes	—	Date & time (ISO 8601) of when the `JobOpening` was first seen. Format: `date-time`.
`result.data.data[].attributes.last_seen_at`	`string`	Yes	—	Date & time (ISO 8601) of when the `JobOpening` was last seen. Format: `date-time`.
`result.data.data[].attributes.last_processed_at`	`string`	Yes	—	Date & time (ISO 8601) of when the `JobOpening` was last sent to processing. Format: `date-time`.
`result.data.data[].attributes.contract_types`	`array`	Yes	—	Zero or more types describing the `JobOpening`.
`result.data.data[].attributes.categories`	`array`	Yes	—	Zero or more organizational categories of the `JobOpening`.
`result.data.data[].attributes.onet_data`	`object`	Yes	—	Inferred ONET data for this `JobOpening`. ONET is a source and standardization of occupational information. More info on the O*NET data: onetonline.org.
`result.data.data[].attributes.onet_data.code`	`string \| null`	Yes	—	O*NET category code representing this `JobOpening`. For full list of possible codes see: https://www.onetonline.org/find/all
`result.data.data[].attributes.onet_data.family`	`string \| null`	Yes	—	O*NET family name matching the code for this `JobOpening`.
`result.data.data[].attributes.onet_data.occupation_name`	`string \| null`	Yes	—	O*NET occupation name matching the code for this `JobOpening`.
`result.data.data[].attributes.posted_at`	`string \| null`	Yes	—	Date & time (ISO 8601) of when the `JobOpening` was posted. Format: `date-time`.
`result.data.data[].attributes.recruiter_data`	`object`	Yes	—	Info about the contact responsible for hiring for this `JobOpening`.
`result.data.data[].attributes.recruiter_data.name`	`string \| null`	Yes	—	Name of the contact responsible for hiring for this `JobOpening`.
`result.data.data[].attributes.recruiter_data.title`	`string \| null`	Yes	—	Title of the contact responsible for hiring for this `JobOpening`.
`result.data.data[].attributes.recruiter_data.contact`	`string \| null`	Yes	—	Contact info for this `JobOpening`, such as email address or Linkedin profile URL.
`result.data.data[].attributes.salary`	`string \| null`	Yes	—	Raw salary string.
`result.data.data[].attributes.salary_data`	`object`	Yes	—	Parsed raw salary data.
`result.data.data[].attributes.salary_data.salary_low`	`number \| null`	Yes	—	Salary range lower bound. If salary is not a range both low and high values will be the same.
`result.data.data[].attributes.salary_data.salary_high`	`number \| null`	Yes	—	Salary range upper bound.
`result.data.data[].attributes.salary_data.salary_currency`	`string \| null`	Yes	—	Salary currency.
`result.data.data[].attributes.salary_data.salary_low_usd`	`number \| null`	Yes	—	Salary range lower bound, converted to USD.
`result.data.data[].attributes.salary_data.salary_high_usd`	`number \| null`	Yes	—	Salary range upper bound, converted to USD.
`result.data.data[].attributes.salary_data.salary_time_unit`	`"hour" \| "day" \| "week" \| "month" \| "year" \| null`	Yes	—	Salary time unit. Allowed: `hour`, `day`, `week`, `month`, `year`, `null`.
`result.data.data[].attributes.seniority`	`"not_set" \| "founder" \| "c_level" \| "partner" \| "president" \| "vice_president" \| "head" \| "director" \| "manager" \| "mid_senior" \| "junior"`	Yes	—	Seniority inferred from the `JobOpening` title. Allowed: `not_set`, `founder`, `c_level`, `partner`, `president`, `vice_president`, `head`, `director`, `manager`, `mid_senior`, `junior`.
`result.data.data[].attributes.status`	`"closed" \| null`	Yes	—	null or “closed” if keyword “job no longer available”, “vacancy listing expired”, “position filled”, etc. is found on `JobOpening` site. Allowed: `closed`, `null`.
`result.data.data[].attributes.language`	`string \| null`	Yes	—	Language in which a `JobOpening` description is written.
`result.data.data[].attributes.location`	`string \| null`	Yes	—	`JobOpening` location. NOTE: It is built from the `location_data` attributes if present. Otherwise, it falls back to the original unnormalized detected location string.
`result.data.data[].attributes.location_data`	`array`	Yes	—	NOTE: Currently contains at most one object.
`result.data.data[].attributes.location_data[].city`	`string \| null`	Yes	—	City of the location.
`result.data.data[].attributes.location_data[].state`	`string \| null`	Yes	—	State of the location.
`result.data.data[].attributes.location_data[].zip_code`	`string \| null`	Yes	—	ZIP code of the location.
`result.data.data[].attributes.location_data[].country`	`string \| null`	Yes	—	Country of the location.
`result.data.data[].attributes.location_data[].region`	`string \| null`	Yes	—	Region of the location.
`result.data.data[].attributes.location_data[].continent`	`string \| null`	Yes	—	Continent of the location.
`result.data.data[].attributes.location_data[].fuzzy_match`	`boolean \| null`	Yes	—	`true` indicates that location data may not have been extracted accurately. `false` indicates that location data has been extracted correctly.
`result.data.data[].attributes.tags`	`array`	Yes	—	Includes keywords found under `JobOpening` description.
`result.data.data[].relationships`	`object`	Yes	—	The data contains references to related objects listed in the `included` property.
`result.data.data[].relationships.company`	`object`	Yes	—	The data contains a reference to related `CompanyLite` object listed in the `included` property.
`result.data.data[].relationships.company.data`	`object`	Yes	—	—
`result.data.data[].relationships.company.data.id`	`string`	Yes	—	ID of the included `CompanyLite` object. Format: `uuid`.
`result.data.data[].relationships.company.data.type`	`"company"`	Yes	—	Type of the included `CompanyLite` object.

The table shows the first 50 fields. Expand the raw schema below for every field.

This output schema is too large for an inline display. Read the complete live contract with deepline describe predictleads_discover_job_openings --json.

Deepline cost

Pricing model: per_result (per result).
Estimated Deepline credits: 0.56 per pricing unit.

​Run this action

​CLI

​Example response

​Input reference

​Output reference

​Deepline cost

​Related documentation

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

Related documentation