# Data Dictionary: Multi-source Employee API On this page, you'll find detailed information about Coresignal's **Multi-source Employee** data.\ Each category includes a table listing the available data fields, their explanations, data types, and sample code snippets. {% hint style="info" %} All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes. Data fields in the example snippets are rearranged for better grouping. {% endhint %} {% tabs %} {% tab title="Data fields per category" %} 1. [Metadata](#metadata) 2. [Identifiers and URLs](#identifiers-and-urls) 3. [Employee information](#employee-information) 4. [Professional contact information](#professional-contact-information) 5. [Locations](#location) 6. [Experience and workplace](#experience-and-workplace) 7. [Full experience information](#full-experience-information) 8. [Workplace details](#workplace-details) 9. [Education](#education) 10. [Salary](#salary) 11. [Profile field changes](#profile-field-changes) 12. [Recent experience changes](#recent-experience-changes) 13. [Recommendations](#recommendations) 14. [Activity](#activity) 15. [Awards](#awards) 16. [Courses](#courses) 17. [Certifications](#certifications) 18. [Languages](#languages) 19. [Patents](#patents) 20. [Publications](#publications) 21. [Projects](#projects) 22. [Organizations](#organizations) 23. [Investments](#investments) 24. [Events and exits](#events-and-exits) {% endtab %} {% endtabs %} ## Metadata | Data field | Description | Data type | | -------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | | `created_at` | The date and time when the employee record was created | String (date) | | `updated_at` | The date and time when the employee record was last fully updated | String (date) | | `checked_at` | The date and time when the employee record was last checked partially | String (date) | | `changed_at` | The date and time when the employee record was last changed | String (date) | | `experience_change_last_identified_at` | The date and time when the employee record change was last identified | String (date) | | `is_deleted` |

Marks if the employee record is deleted or private
1 – the record is deleted
0 – the record is not deleted

| Number (integer) | | `is_parent` |

Notes if the employee record is the main employee profile:
1 – the record is parent (main)
0 – the record is not parent

| Number (integer) | **See a snippet of the dataset for reference:** {% code title="Metadata" %} ```json "created_at": "2024-07-27T01:56:27.000", "updated_at": "2024-10-23T05:50:09.000", "checked_at": "2025-09-23T05:50:09.000", "changed_at": "2025-10-01T06:30:1.000", "experience_change_last_identified_at": "2024-10-25T06:30:10.000", "is_deleted": 0, "is_parent": 1 ``` {% endcode %} ## Identifiers and URLs | Data field | Description | Data type | | ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- | ---------------- | | `id` |

Coresignal's identification key for an employee profile record.
Taken from the professional network dataset.

| Number (integer) | | `parent_id` | Parent category identification key | Number (integer) | | `historical_ids` | Historical identification keys that are related to the same profile after URL change | Array of longs | | `professional_network_url` | Most recent profile URL on professional network | String | | `professional_network_shorthand_names` | Historical variations of shorthand names for the employee | Array of strings | | `professional_network_canonical_shorthand_name` | The most recent version of employee’s shorthand name | String | | `public_profile_id` | Public profile ID | Number (long) | | `facebook_url` | Facebook URL | String | | `twitter_url` | Twitter URL | String | | `financial_website_url` | Financial website URL | String | | `website` | Employee's website | String | **See a snippet of the dataset for reference:** {% code title="Identifiers & URLs" %} ```json "id": 12389891, "parent_id": 12389891, "public_profile_id": 123456789, "historical_ids": [ 12389891, 11589843 ], "professional_network_url": "https://www.professional_network.com/in/john-doe-18729383", "professional_network_shorthand_names": [ "real-john-doe" "john-doe-1992" ], "professional_network_canonical_shorthand_name": "john-doe-18729383", "facebook_url": "https://www.facebook.com/john-doe", "twitter_url": "https://www.x.com/john-doe", "financial_website_url": "https://www.financial-website.com/person/john-doe", "website": "https://www.john-doe-website.com" ``` {% endcode %} ### Profile score | Data field | Description | Data type | | --------------- | ----------------------------------------------------------------------------------------------------------------------- | --------- | | `profile_score` | Model-derived employee profile quality score based on profile completeness and activity signals. Score range: `0` – `1` | Double | **See a snippet of the dataset for reference:** {% code title="Profile score" %} ```json "profile_score": 0.5 ``` {% endcode %} ## Employee information | Data field | Description | Data type | | --------------------- | ------------------------------------------------------------------------ | ---------------- | | `full_name` | Employee's full name | String | | `first_name` |

Employee's first name
Parsed from the full\_name

| String | | `first_name_initial` |

First name initial
Parsed from first\_name

| String | | `middle_name` |

Employee's middle name
Parsed from the full\_name

| String | | `middle_name_initial` |

Middle name initial
Parsed from middle\_name

| String | | `last_name` |

Employee's last name
Parsed from the full\_name

| String | | `last_name_initial` |

Last name initial
Parsed from last\_name

| String | | `picture_url` | Picture URL | String | | `connections_count` | Count of profile connections | Number (integer) | | `followers_count` | Count of profile followers | Number (integer) | | `interests` | Employee's interests | Array of strings | **See a snippet of the dataset for reference:** {% code title="Employee information" %} ```json "full_name": "John Doe", "first_name": "John", "first_name_initial": "J", "middle_name": "Michael", "middle_name_initial": "M", "last_name": "Doe", "last_name_initial": "D", "picture_url": "https://static.lnk.com/aero-v1/sc/h/9c8pery4andzj6ohjkjp54ma2" "connections_count": 472, "followers_count": 3190, "interests": [ "hiking", "snowboarding", "cycling", ] ``` {% endcode %} ## Professional contact information {% hint style="info" %} Coresignal **collects only publicly available, strictly business-related data** published or released by companies or individuals at their discretion online. The contact information includes **only professional emails**.\ No sensitive or private/ located within the login secured areas information is collected or transmitted. {% endhint %} | Data field | Description | Data type | | ----------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | | `primary_professional_email` | Employee's business email address tied to their workplace | String | | `primary_professional_email_status` | The confidence level in the accuracy of the employee's business email address. The field will return four options: `verified`, `matched_email, ``matched_pattern,` or`guessed_common_pattern`. | String | | `professional_emails_collection` | Collection of employee's business email addresses | Array of structs | | `professional_email` | Employee's business email address | String | | `professional_email_status` |

The confidence level in the accuracy of the employee's professional email address. The field will return four options:

| String | | `order_of_priority` | Order of priority based on confidence in email validity | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Professional contact information" %} ```json "primary_professional_email": "johndoe@company1.com", "primary_professional_email_status": "matched_pattern", "professional_emails_collection": [ { "professional_email": "johndoe@company1.com", "professional_email_status": "matched_pattern", "order_of_priority": 1 }, { "professional_email": "john.doe1@company1.com", "professional_email_status": "matched_pattern", "order_of_priority": 2 }, { "professional_email": "johndoe123@company1.com", "professional_email_status": "matched_pattern", "order_of_priority": 3 } ] ``` {% endcode %} ## Location | Data field | Description | Data type | | ----------------------- | ----------------------------------------------------------------------------------- | ---------------- | | `location_country` | Associated country | String | | `location_city` | Employee location city | String | | `location_state` | Employee location state | String | | `location_country_iso2` | ISO 2-letter code of the location country, based on their `location_country` value. | String | | `location_country_iso3` | ISO 3-letter code of the location country, based on their `location_country`value. | String | | `location_full` | Full location | String | | `location_regions` | Associated geographical regions based on their `location_country` value | Array of strings | **See a snippet of the dataset for reference:** {% code title="Location" %} ```json "location_country": "United States", "location_city": "San Diego", "location_state": "California", "location_country_iso2": "US", "location_country_iso3": "USA", "location_full": "San Diego, California, United States", "location_regions": [ { "region": "Americas" }, { "region": "Northern America" }, { "region": "AMER" } ] ``` {% endcode %} ## Experience and workplace ### Active experience overview | Data field | Description | Data type | | ------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | | `headline` | Profile headline | String | | `summary` | Main description (employee summary) | String | | `services` | Offered services | String | | `is_working` |

Marks if the employee is currently employed
1 – the employee is currently working
0 – the employee is currently not working

| Number (integer) | | `active_experience_company_id` | Coresignal's identification key for a company to identify where the employee is currently working | Number (integer) | | `active_experience_title` | Title of employee's current position | String | | `active_experience_description` | Description of the current position | String | | `active_experience_department` | A list of employee's departments, based on `actve_position_title` | String | | `active_experience_management_level` | A list of employee's management levels, based on `active_experience_title` | String | | `is_decision_maker` |

Marks if the employee is a decision maker, based on active\_experience\_title
1 – the employee is a decision maker
0 – the employee is not a decision maker

| Number (integer) | **See a snippet of the dataset for reference:** {% code title="Active experience overview" %} ```json "headline": "Data Analyst | Machine Learning Enthusiast", "summary": "

Passionate about uncovering insights from data and applying machine learning techniques to solve global problems.

", "services": "Data Analysis, Machine Learning Consulting, Business Intelligence", "is_working": 1, "active_experience_company_id": 4127532, "active_experience_title": "Senior Data Analyst", "active_experience_description": "Leading data-driven projects, building predictive models, and optimizing business intelligence strategies.", "active_experience_department": "Engineering and Technical", "active_experience_management_level": "Senior", "is_decision_maker": 1 ``` {% endcode %} ### Skills | Data field | Description | Data type | | ------------------- | ------------------------------------------------------------------ | ---------------- | | `inferred_skills` | Lists employees' skills based on the descriptions from the profile | Array of strings | | `historical_skills` | Historical skills | Array of strings | **See a snippet of the dataset for reference:** {% code title="Skills" %} ```json "inferred_skills": [ "cloud computing", "data analysis", "deep learning", "software development", "system architecture", "troubleshooting", "web development" ] ``` {% endcode %} ### Experience duration | Data field | Description | Data type | | ------------------------------------------------------------- | ------------------------------------------------------------------- | ---------------- | | `total_experience_duration_months` | Total normalized experience duration of all Employee's experiences | Number (integer) | | `total_experience_duration_months_breakdown_department` | Total normalized experience duration by employee's department | Array of structs | | `department` | Department | String | | `total_experience_duration_months` | Experience duration in months | String | | `total_experience_duration_months_breakdown_management_level` | Total normalized experience duration by Employee's management level | Array of structs | | `management_level` | Employee's management level | String | | `total_experience_duration_months` | Experience duration in months | String | **See a snippet of the dataset for reference:** {% code title="Experience duration" %} ```json "total_experience_duration_months": 85, "total_experience_duration_months_breakdown_department": [ { "department": "C-Suite", "total_experience_duration_months": 13 }, { "department": "Marketing", "total_experience_duration_months": 30 }, { "department": "Finance & Accounting", "total_experience_duration_months": 14 }, { "department": "Engineering and Technical", "total_experience_duration_months": 28 } ], "total_experience_duration_months_breakdown_management_level": [ { "management_level": "C-Level", "total_experience_duration_months": 10 }, { "management_level": "Intern", "total_experience_duration_months": 3 }, { "management_level": "Senior", "total_experience_duration_months": 4 }, { "management_level": "Specialist", "total_experience_duration_months": 40 }, { "management_level": "Manager", "total_experience_duration_months": 18 } ] ``` {% endcode %} ## Full experience information | Data field | Description | Data type | | ------------------- | ------------------------------------------------- | ---------------- | | `experience` | Work experience the Employee has | Array of structs | | `active_experience` | Identifies if this is a current (active) position | Integer | | `position_title` | Employee's position title | String | | `department` | Employees department | String | | `management_level` | Employee's management level | String | | `location` | Job/workplace location | String | | `date_from` | Employment start date | String (date) | | `date_from_year` | Employment start year | Integer | | `date_from_month` | Employment start month | Integer | | `date_to` | Employment end date | String (date) | | `date_to_year` | Employment end year | Integer | | `date_to_month` | Employment end month | Integer | | `duration_months` | Employment duration in months | Integer | | `description` | Employment description | String | | `company_logo_url` | URL pointing to the logo of the company/employer | String | **See a snippet of the dataset for reference:** {% code title="Full experience information" %} ```json "experience": [ { "active_experience": 0, "position_title": "Senior Data Analyst", "department": "Data Science", "management_level": "Mid-Level", "location": "San Francisco, California, United States", "date_from": "March 2020", "date_from_year": 2020, "date_from_month": 3, "date_to": "July 2022", "date_to_year": 2022, "date_to_month": 7, "duration_months": 126, "company_logo_url": "https://example.com/image/company-logo" } ] ``` {% endcode %} ## Workplace details ### Metadata and firmographics | Data field | Description | Data type | | -------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | | `company_id` | Company record identification key in Coresignal's database | Integer | | `company_name` | Company name | String | | `company_type` | Company type | String | | `company_founded_year` | Founding year | String (date) | | `company_size_range` | Company size based on employee count range (as selected by the company profile administrator) | String | | `company_employees_count` | Number of employees that associated their experience with the company | Integer | | `company_categories_and_keywords` | Categories and keywords are assigned to the company profile and products across various platforms | Array of strings | | `company_employees_count_change_yearly_percentage` | Company employee count change (percentage) | Number (double) | | `company_industry` | Company's industry | String | | `company_last_updated_at` | The last update date of the record in the `YYYY-MM-DD` format | String (date) | | `company_is_b2b` |

Indicates if the company operates in a business-to-business model:
1 – b2b company
0 – b2c company

| Integer | | `order_in_profile` | The order number of the workplace in the profile | Integer | **See a snippet of the dataset for reference:** {% code title="Metadata & firmographics" %} ```json "company_id": 87272276, "company_name": "Company123, LLC", "company_type": "Privately Held", "company_founded_year": "2023", "company_size_range": "51-200 employees", "company_employees_count": 157, "company_categories_and_keywords": [ "Data Analysis", "AI", "Management", "Consulting", ], "company_employees_count_change_yearly_percentage": 17.43222222222222 "company_industry": "Manufacturing", "company_last_updated_at": "2025-02-03", "company_is_b2b": 1, "order_in_profile": 1 ``` {% endcode %} ### Social media | Data field | Description | Data type | | ------------------------- | -------------------------------------------------------- | ---------------- | | `company_followers_count` | Company's profile follower count on professional network | Integer | | `company_website` | Company's website | String | | `company_facebook_url` | Company's Facebook URL | Array of strings | | `company_twitter_url` | Company's X (Twitter) URL | Array of strings | | `company_linkedin_url` | Company's LinkedIn URL | String | **See a snippet of the dataset for reference:** {% code title="Social media" %} ```json "company_followers_count": 527712, "company_website": "https://www.company1.com", "company_facebook_url": [ "https://www.facebook.com/company1global", "https://www.facebook.com/company1" ], "company_twitter_url": [ "https://www.x.com/company1" ], "company_linkedin_url": "https://www.linkedin.com/company/company1" ``` {% endcode %} ### Financials | Data field | Description | Data type | | ---------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------- | ---------------- | |

company\_annual\_revenue\_source\_1
company\_annual\_revenue\_source\_5

| Company's revenue from a specific source | Array of objects | |

company\_annual\_revenue\_currency\_source\_1

company\_annual\_revenue\_currency\_source\_5

| Revenue currency | String | | `company_last_funding_round_date` | Date when the last funding round was announced in `YYYY-MM-DD` format | String (date) | | `company_last_funding_round_amount_raised` | Amount raised in the last funding round | Integer (long) | | `company_stock_ticker` | Company's stock ticker information | Array of objects | | `exchange` | Stock exchange | String | | `ticker` | Stock ticker | String | **See a snippet of the dataset for reference:** {% code title="Financials" %} ```json "annual_revenue_source_5": 32590000, "annual_revenue_currency_source_5": "$", "annual_revenue_source_1": 878728373, "annual_revenue_currency_source_1": "$", "company_last_funding_round_date": "2014-03-25", "company_last_funding_round_amount_raised": 200 000, "stock_ticker": [ { "exchange": "NASDAQ", "ticker": "AAPL" } ] ``` {% endcode %} ### Workplace locations | Data field | Description | Data type | | ------------------------- | ----------------------------------------------------------- | ---------------- | | `company_hq_full_address` | Full address of the company's headquarters | String | | `company_hq_country` | The country where the company's headquarters is located | String | | `company_hq_regions` | Detailed region where the company's headquarters is located | Array of strings | | `company_hq_country_iso2` | ISO 2-letter code of the headquarters country | String | | `company_hq_country_iso3` | ISO 3-letter code of the headquarters country | String | | `company_hq_city` | Headquarters city | String | | `company_hq_state` | Headquarters state | String | | `company_hq_street` | Headquarters street address | String | | `company_hq_zipcode` | Headquarters zip code | String | **See a snippet of the dataset for reference:** {% code title="Locations" %} ```json "company_hq_full_address": "123 Data Drive, Analytics City, CA 94016, USA", "company_hq_country": "United States", "company_hq_regions": [ "Americas", "Northern America", "AMER"], "company_hq_country_iso2": "US", "company_hq_country_iso3": "USA", "company_hq_city": "Analytics City", "company_hq_state": "California", "company_hq_street": "123 Data Drive", "company_hq_zipcode": "94016", ``` {% endcode %} ## Education | Data field | Description | Data type | | -------------------------- | ----------------------------------------------------------------------------------------------- | ---------------- | | `last_graduation_date` | Last graduation date | String (date) | | `education_degrees` | List of education degrees held by the person | Array of strings | | `education` | Employee's education | Array of objects | | `degree` | Degree name | String | | `description` | Degree description | String | | `institution_url` | Institution's profile URL | String | | `institution_logo_url` | URL pointing to the logo of the educational institution (university, school, training provider) | String | | `institution_name` | Institution's name | String | | `institution_full_address` | Institution's full address | String | | `institution_country_iso2` | ISO 2-letter code of the institution's country | String | | `institution_country_iso3` | ISO 3-letter code of the institution's country | String | | `institution_regions` | Institution's region | Array of strings | | `institution_city` | Institution's city | String | | `institution_state` | Institution's state | String | | `institution_street` | Institution's street | String | | `institution_zipcode` | Institution's zip code | String | | `date_from_year` | Enrollment date | Number (integer) | | `date_to_year` | Graduation date | String (date) | | `activities_and_societies` | Activities and societies that are connected with the employee | String | | `order_in_profile` | Order in profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Education" %} ```json "last_graduation_date": 2022, "education_degrees": [ "Bachelor of Science, Computer Science Engineering, 9.12 (Rank: 4/80)", "Senior Secondary, Mathematics, 93%", "Higher Secondary, Science, 96%" ], "education": [ { "degree": "Bachelor of Science, Computer Science Engineering, 9.12 (Rank: 4/80)", "description": "Focused on core sciences with a strong foundation in Physics and Chemistry.", "institution_url": "https://www.topuniversity.edu", "institution_logo_url": "https://example.com/image/institution-logo", "institution_name": "Top University", "institution_full_address": "Top University, 123 Main St, Cityville, State 12345, USA", "institution_country_iso2": "US", "institution_country_iso3": "USA", "institution_regions": [ "North America", "East Coast" ], "institution_city": "Cityville", "institution_state": "State", "institution_street": "123 Main St", "institution_zipcode": "12345", "date_from_year": 2014, "date_to_year": 2016, "activities_and_societies": "Science Fair, Debate Team", "order_in_profile": 1 }, ] ``` {% endcode %} ## Salary ### Projected base salary | Data field | Description | Data type | | ---------------------------------- | ------------------------------------------------------------------------ | --------------- | | `projected_base_salary_p25` | Minimum projected base salary for the current position (25th percentile) | Number (double) | | `projected_base_salary_median` | Median projected base salary for the current position | Number (double) | | `projected_base_salary_p75` | Maximum projected base salary for the current position (75th percentile) | Number (double) | | `projected_base_salary_period` | Data collection period | String | | `projected_base_salary_currency` | Salary currency | String | | `projected_base_salary_updated_at` | Data last update date | String (date) | **See a snippet of the dataset for reference:** {% code title="Projected base salary" %} ```json "projected_base_salary_p25": 105432.56, "projected_base_salary_median": 120785.90, "projected_base_salary_p75": 145430.78, "projected_base_salary_period": "ANNUAL", "projected_base_salary_currency": "USD", "projected_base_salary_updated_at": "2025-02-03" ``` {% endcode %} ### Projected additional salary | Data field | Description | Data type | | ---------------------------------------- | ------------------------------------------------------------------------------ | ---------------- | | `projected_additional_salary` | Projected additional salary | Array of structs | | `projected_additional_salary_type` | Projected additional salary type for the current position | String | | `projected_additional_salary_p25` | Minimum projected additional salary for the current position (25th percentile) | Number (double) | | `projected_additional_salary_median` | Median projected additional salary for the current position | Number (double) | | `projected_additional_salary_p75` | Maximum projected additional salary for the current position (75th percentile) | Number (double) | | `projected_additional_salary_period` | Data collection period | String | | `projected_additional_salary_currency` | Salary currency | String | | `projected_additional_salary_updated_at` | Data last update date | String (date) | **See a snippet of the dataset for reference:** {% code title="Projected additional salary" %} ```json "projected_additional_salary": [ { "projected_additional_salary_type": "Cash Bonus", "projected_additional_salary_p25": 7654.21, "projected_additional_salary_median": 10234.56, "projected_additional_salary_p75": 14123.78 }, { "projected_additional_salary_type": "Stock Bonus", "projected_additional_salary_p25": 8892.10, "projected_additional_salary_median": 11754.93, "projected_additional_salary_p75": 16123.12 } ] "projected_additional_salary_period": "ANNUAL", "projected_additional_salary_currency": "USD", "projected_additional_salary_updated_at": "2024-12-06" ``` {% endcode %} ### Projected total salary | Data field | Description | Data type | | ----------------------------------- | ------------------------------------------------------------------------------- | --------------- | | `projected_total_salary_p25` | Minimum projected total salary value for the current position (25th percentile) | Number (double) | | `projected_total_salary_median` | Median projected total salary value for the current position | Number (double) | | `projected_total_salary_p75` | Maximum projected total salary value for the current position (75th percentile) | Number (double) | | `projected_total_salary_period` | Data collection period | String | | `projected_total_salary_currency` | Salary currency | String | | `projected_total_salary_updated_at` | Data last update date | String (date) | **See a snippet of the dataset for reference:** {% code title="Projected total salary" %} ```json "projected_total_salary_p25": 142763.21, "projected_total_salary_median": 153290.88, "projected_total_salary_p75": 165432.19, "projected_total_salary_period": "ANNUAL", "projected_total_salary_currency": "USD", "projected_total_salary_updated_at": "2025-02-12", ``` {% endcode %} ## Profile field changes | Data field | Description | Data type | | ------------------------------------------ | ----------------------------------------------- | ---------------- | | `profile_root_field_changes_summary` | Summary of the field-level changes | Array of structs | | `field_name` | Name of the data field | String | | `change_type` | Type of the data field change | String | | `last_changed_at` | Date of the last data field change | String (date) | | `profile_collection_field_changes_summary` | Summary of changes in profile collection fields | Array of structs | | `field_name` | Name of the collection data field | String | | `last_changed_at` | Data of the last collection data field change | String | **See a snippet of the dataset for reference:** {% code title="Profile field changes" %} ```json "profile_root_field_changes_summary": [ { "field_name": "followers_count", "change_type": "updated", "last_changed_at": "2023-07-18T09:22:45.567" }, { "field_name": "summary", "change_type": "updated", "last_changed_at": "2025-02-18T09:22:45.567" } ], "profile_collection_field_changes_summary": [ { "field_name": "experience", "last_changed_at": "2024-01-05T17:48:12.892" }, { "field_name": "activity", "last_changed_at": "2025-02-05T17:48:12.892" } ] ``` {% endcode %} ## Recent experience changes | Data field | Description | Data type | | ----------------------------- | -------------------------------------------------------------- | ---------------- | | `experience_recently_started` | Collection of identified recently started Employee experiences | Array of structs | | `company_id` | Coresignal's identification key for a company record | String | | `company_name` | Company name | String | | `company_url` | Professional network URL of the company | String | | `company_shorthand_name` | Shorthand name of the company's Professional network URL | String | | `date_from` | Start date of the experience record | String | | `date_to` | End date of the experience record | String | | `title` | Position title in the company | String | | `identification_date` | Date when experience change was identified | String | | `experience_recently_closed` | Collection of employee experiences that ended recently | Array of structs | | `company_id` | Coresignal's identification key for a company record | String | | `company_name` | Company name | String | | `company_url` | Professional network URL of the company | String | | `company_shorthand_name` | Shorthand name of the company's Professional network URL | String | | `date_from` | Start date of the experience record | String | | `date_to` | End date of the experience record | String | | `title` | Position title in the company | String | | `identification_date` | Date when experience change was identified | String | **See a snippet of the dataset for reference:** {% code title="Recent experience changes" %} ```json "experience_recently_started": [ { "company_id": 3124502, "company_name": "Company1, LLC", "company_url": "https://www.professional_network.com/company/company1-llc", "company_shorthand_name": "company1-llc", "date_from": "Nov 2024", "date_to": "Dec 2024", "title": "Senior Software Engineer", "identification_date": "2024-11-19T15:34:29.412" }, ], "experience_recently_closed": [ { "company_id": 3124504, "company_name": "Company3, LLC", "company_url": "https://www.professional_network.com/company/company3-llc", "company_shorthand_name": "company3-llc", "date_from": "Jul 2021", "date_to": "Oct 2024", "title": "Software Engineer", "identification_date": "2024-12-14T10:48:37.215" } ] ``` {% endcode %} ## Recommendations | Data field | Description | Data type | | ----------------------- | ----------------------------------------------------------------- | ---------------- | | `recommendations_count` | Number of recommendations from other users | Number (integer) | | `recommendations` | List of recommendations received | Array of structs | | `recommendation` | Recommendation text | String | | `referee_full_name` | The full name of the person who wrote the recommendation | String | | `referee_url` | The URL of the profile of the person who wrote the recommendation | String | | `order_in_profile` | The exact position of the recommendation in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Recommendations" %} ```json "recommendations_count": 2, "recommendations": [ { "recommendation": "“I had the pleasure of collaborating with John during his time at Tech Innovations, where he displayed a rare combination of creativity and technical expertise. He consistently demonstrated outstanding problem-solving skills, particularly in software engineering and AI. His attention to detail and collaborative spirit made him a valuable asset to the team. John is also a great mentor who is always ready to share his knowledge with others, making him a true team player.”", "referee_full_name": "Jane Doe 1", "referee_url": "https://www.professional_network.com/in/jane-doe-1", "order_in_profile": 1 }, { "recommendation": "“John’s drive and determination have impressed me from our first interaction during a project at Company1 Solutions. He has an extraordinary ability to tackle complex challenges and has a passion for both technology and team collaboration. His contributions were key to the success of several high-profile projects. He is an individual who thrives in dynamic environments and continuously seeks to innovate and improve processes.”", "referee_full_name": "Jane Doe 2", "referee_url": "https://www.professional_network.com/in/jane-doe-2", "order_in_profile": 2 } ] ``` {% endcode %} ## Activity | Data field | Description | Data type | | ------------------ | ------------------------------------------------- | ---------------- | | `activity` | User's activity (posts) | Array of structs | | `activity_url` | Post URL | String | | `title` | Post title | String | | `action` | Activity type | String | | `order_in_profile` | The exact position of the activity in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Activity" %} ```json "activity": [ { "activity_url": "https://www.professional_network.com/posts/johndoe_ai-innovations-and-the-future-of-tech-activity-1234567890123456789-XYZ", "title": "Excited to share my thoughts on the future of AI and its impact on industries worldwide. The advancements in machine learning are opening new doors…", "action": "Liked by", "order_in_profile": 1 } ] ``` {% endcode %} ## Awards | Data field | Description | Data type | | ------------------ | ---------------------------------------------- | ---------------------- | | `awards_count` | Count of employee awards | String | | `awards` | Awards held by the person | Array of structs | | `title` | Award title | String | | `issuer` | Award issuer | String | | `description` | Award description | String | | `date` | Award date | String | | `date_year` | Award year | StringNumber (integer) | | `date_month` | Award month | Number (integer) | | `order_in_profile` | The exact position of the award in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Awards" %} ```json "awards_count": "1", "awards": [ { "title": "Outstanding Achievement Award", "issuer": "Top University", "description": "Recognized for exceptional contributions to student initiatives and leadership in organizing university-wide events.", "date": "March 15, 2024", "date_year": 2024, "date_month": 3, "order_in_profile": 1 } ] ``` {% endcode %} ## Courses | Data field | Description | Data type | | ------------------ | ----------------------------------------------- | ---------------- | | `courses` | Courses | Array of structs | | `organizer` | Course organizer | String | | `title` | Course title | String | | `order_in_profile` | The exact position of the course in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Courses" %} ```json "courses": [ { "organizer": "AI Certification", "title": "Machine Learning Fundamentals", "order_in_profile": 1 }, { "organizer": "CS Academ", "title": "Advanced Algorithms and Data Structures", "order_in_profile": 2 }, ] ``` {% endcode %} ## Certifications | Data field | Description | Data type | | ---------------------- | --------------------------------------------------------------------------------------- | ---------------- | | `certifications_count` | Count of user certifications | String | | `certifications` | Certifications | Array of structs | | `title` | Certification title | String | | `issuer` | Certification issuer | String | | `issuer_url` | Issuer profile URL | String | | `credential_id` | Credential identification key | String | | `certificate_url` | Certification URL | String | | `certificate_logo_url` | URL pointing to the logo of the certification provider (AWS, Microsoft, Coursera, etc.) | String | | `date_from` | Certification issue date | String (date) | | `date_from_year` | Issue year | Number (integer) | | `date_from_month` | Issue month | Number (integer) | | `date_to` | Certification expiry date | String (date) | | `date_to_year` | Expiry year | Number (integer) | | `date_to_month` | Expiry month | Number (integer) | | `order_in_profile` | The exact position of the certification in the profile | Number Array | **See a snippet of the dataset for reference:** {% code title="Certifications" %} ```json "certifications_count": "1", "certifications": [ { "title": "Advanced Data Analysis", "issuer": "Certification Company 123", "issuer_url": "https://www.certificationcompany123.com", "credential_id": "EFGH98765432", "certificate_url": "https://www.certificationcompany123.com/certificates/f44f9027fba14efb953da9db849e5ed2", "certificate_logo_url": "https://example.com/image/certificate-logo", "date_from": "Nov 2023", "date_from_year": 2023, "date_from_month": 11, "date_to": "Nov 2024", "date_to_year": 2024, "date_to_month": 11, "order_in_profile": 1 } ] ``` {% endcode %} ## Languages | Data field | Description | Data type | | ------------------ | ------------------------------------------------- | ---------------- | | `languages` | Language knowledge | Array of structs | | `language` | Listed language | String | | `proficiency` | Language proficiency | String | | `order_in_profile` | The exact position of the language in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Languages" %} ```json "languages": [ { "language": "English", "proficiency": "Full professional proficiency", "order_in_profile": 1 }, { "language": "Spanish", "proficiency": "Limited working proficiency", "order_in_profile": 2 }, { "language": "French", "proficiency": "Professional working proficiency", "order_in_profile": 3 } ] ``` {% endcode %} ## Patents | Data field | Description | Data type | | ------------------ | ----------------------------------------------- | ---------------- | | `patents_count` | Number of authored patents | Number (integer) | | `patents_topics` | Patent topics | Array of strings | | `patents` | Authored patents | Array of structs | | `title` | Patent title | String | | `status` | Patent status | String | | `description` | Patent description | String | | `patent_url` | Patent URL | String | | `date` | Patent filing date | String (date) | | `date_year` | Filling year | Number (integer) | | `date_month` | Filling month | Number (integer) | | `patent_number` | Patent number | String | | `order_in_profile` | The exact position of the patent in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Patents count" %} ```json "patents_count": 1, "patents_topics": "Data Analysis", "patents": [ { "title": "Advanced Data Analysis Using Neural Networks", "status": "Granted", "description": "A novel approach to data analysis leveraging deep learning techniques to improve accuracy in predictive modeling and data interpretation.\\n

", "patent_url": "https://example123.com/patent/data-analysis-neural-networks", "date": "September 10, 2023", "date_year": 2023, "date_month": 9, "patent_number": "US112233445A1", "order_in_profile": 1 } ] ``` {% endcode %} ## Publications | Data field | Description | Data type | | --------------------- | ---------------------------------------------------- | ---------------- | | `publications_count` | Count of publications authored by the employee | Number (integer) | | `publications_topics` | Publication topics | Array of strings | | `publications` | Authored publications | Array of structs | | `title` | Publication title | String | | `description` | Publication description | String | | `publication_url` | Publication website URL | String | | `publisher_name` | Publication publisher | Array of strings | | `date` | Publication release date | String (date) | | `date_year` | Release year | Number (integer) | | `date_month` | Release month | Number (integer) | | `order_in_profile` | The exact position of the publication in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Publications" %} ```json "publications_count": 1, "publications_topics": [ "Machine Learning in Healthcare Applications" ], "publications": [ { "title": "Machine Learning-Based Heart Disease Prediction", "description": "This research focuses on utilizing machine learning techniques to predict heart diseases by analyzing EKG signals, a part of my project from June'21 to December'21.\\n

", "publication_url": "https://www.researchpaper123.net/publication/343632915_Machine_Learning", "publisher_names": [ "John Doe", "Jane Doe" ], "date": "December 15, 2021", "date_year": 2021, "date_month": 12, "order_in_profile": 1 } ] ``` {% endcode %} ## Projects | Data field | Description | Data type | | ------------------ | ---------------------------------------------------- | ---------------- | | `projects_count` | Count of total projects listed in the profile | Number (integer) | | `projects_topics` | Topics related to the projects listed in the profile | Array of strings | | `projects` | Projects created by the profile | Array of structs | | `name` | Project name | String | | `description` | Project description | String | | `project_url` | Project website URL | String | | `date_from` | Project start date | String (date) | | `date_from_year` | Project start year | Number (integer) | | `date_from_month` | Project start month | Number (integer) | | `date_to` | Project end date | String (date) | | `date_to_year` | Project end year | Number (integer) | | `date_to_month` | Project end month | Number (integer) | | `order_in_profile` | The exact position of the project in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Projects" %} ```json "projects_count": 1, "projects_topics": [ "Predictive Analytics in Complex Systems", "Real-time Facial Expression Analysis for Emotional Intelligence Systems", "Design and Simulation of Adaptive Actuators for Smart Materials", "Audio Signal Separation for Enhanced Speech Recognition", "Non-Invasive Glucose Monitoring Using Spectroscopic Data Analysis" ], "projects": [ { "name": "Predictive Analytics for Fault Detection in Complex Mechanical Systems", "description": "As part of a research initiative, a predictive system was developed to identify anomalies in mechanical systems. The project utilized historical failure data and machine learning models.

", "project_url": "https://www.projecturl123.net/project/123456_Analytics", "date_from": "Oct 2018", "date_from_year": 2018, "date_from_month": 10, "date_to": "May 2019", "date_to_year": 2019, "date_to_month": 5, "order_in_profile": 1 } ] ``` {% endcode %} ## Organizations | Data field | Description | Data type | | ------------------- | ---------------------------------------------------------- | ---------------- | | `organizations` | Memberships in organizations | Array of structs | | `organization_name` | Organization title | String | | `position` | Position in the organization | String | | `description` | Description of the activity/experience in the organization | String | | `date_from` | Membership start date | String (date) | | `date_from_year` | Membership start year | Number (integer) | | `date_from_month` | Membership start month | Number (integer) | | `date_to` | Membership end date | String (date) | | `date_to_year` | Membership end year | Number (integer) | | `date_to_month` | Membership end month | Number (integer) | | `order_in_profile` | The exact position of the organization in the profile | Number (integer) | **See a snippet of the dataset for reference:** {% code title="Organizations" %} ```json "organizations": [ { "organization_name": "Tech Club", "position": "Event Coordinator", "description": "Led and organized data-driven workshops and events, focusing on data analytics and machine learning applications in various industries.", "date_from": "Feb 2016", "date_from_year": 2016, "date_from_month": 2, "date_to": "Mar 2018", "date_to_year": 2018, "date_to_month": 2, "order_in_profile": 1 } ] ``` {% endcode %} {% code title="Organizations" %} ```json "organizations": [ { "organization_name": "Tech Club", "position": "Event Coordinator", "description": "Led and organized data-driven workshops and events, focusing on data analytics and machine learning applications in various industries.", "date_from": "Feb 2016", "date_from_year": 2016, "date_from_month": 2, "date_to": "Mar 2018", "date_to_year": 2018, "date_to_month": 2, "order_in_profile": 1 } ] ``` {% endcode %} ## Investments ### Personal investments | Data field | Description | Data type | | ---------------------- | -------------------------------------------- | -------------- | | `personal_investments` | Personal investments list | Struct | | `announced_date` | Date when the investment was announced | String | | `company_name` | Name of the company receiving the investment | String | | `lead_investor` | Informs if the person was a lead investor | Integer | | `funding_round` | Name or type of the funding round | String | | `amount_raised` | Amount of money raised | Integer (long) | **See a snippet of the dataset for reference:** {% code title="Personal investments" %} ```json "personal_investments": [ { "announced_date": "Aug 1, 2025", "company_name": "Fake Corp", "lead_investor": 0, "funding_round": "First Round - Investment Transfer", "amount_raised": 100000 } ] ``` {% endcode %} ### Partner investments | Data field | Description | Data type | | --------------------- | -------------------------------------------- | -------------- | | `partner_investments` | Partner investments list | Struct | | `announced_date` | Date when the investment was announced | String | | `company_name` | Name of the company receiving the investment | String | | `lead_investor` | Informs if the partner was a lead investor | Integer | | `funding_round` | Name or type of the funding round | String | | `amount_raised` | Amount of money raised | Integer (long) | | `investor_name` | Name of the investor | String | **See a snippet of the dataset for reference:** {% code title="Partner investments" %} ```json "partner_investments": [ { "announced_date": "Aug 1, 2025", "company_name": "Fake Company", "lead_investor": 0, "funding_round": "Round - Fake Company", "amount_raised": 20000, "investor_name": "Example Capital" } ] ``` {% endcode %} ## Events and Exits | Data field | Description | Data type | | --------------------- | ---------------------------------------------------------------------------------------------- | ---------------- | | **`events`** | Information about events | Object | | `name` | Event's name | String | | `role` | Role in the event | String | | `date` | Date of the event | String | | `location` | Location of the event | String | | **`exits`** | Name Section containing information about company exits (e.g., IPO, acquisition) the investion | Array of objects | | `company_name` | Name of the company where the exit happened | String | | `company_description` | Short description of the company | String | **See a snippet of the dataset for reference:** {% code title="Events and Exits" %} ```json "events": [ { "name": "WEB event 2023", "role": "Speaker", "date": "Nov 1, 2023", "location": "London" } ], "exits": [ { "company_name": "Example Organization", "company_description": "Example Organization is a platform designed to buy and sell new technologies." } ] ``` {% endcode %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.coresignal.com/employee-api/multi-source-employee-api/data-dictionary-multi-source-employee-api.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.