Job Parsing
Parse job descriptions and vacancies with a few lines of code.
Depending on their origin, jobs come in various structured formats. Therefore, a standardization step is necessary to unify your talent data channels.
By using Text Parsing, this article shows the different steps to design, enrich and standardize all your job offers into job objects. These objects work well with all HrFlow.ai layers (e.g., Searching, Scoring, Embedding, etc.).
Moreover, through a dashboard, you can track your recruiting strategy in real-time and more efficiently.
Prerequisites
API Endpoint
Get more information about the endpoint 🧠 Parse a raw Text.
Step 1: Configure your Postman Environment
Following the steps from the HrFlow.ai Postman publication will make you land on this page:
First, click on the "Environments" tab on the left side of your Postman window. Then, fill in the Empty - Environment template with the correct values. The compulsory variables for Job Parsing are:
x-api-key: follow the steps from 🔑 API Authentication to retrieve itx-user-email: follow the steps from 🔑 API Authentication to retrieve itboard_key: key of the Board where your Jobs will be stored
Finally, save the environment and ensure that you selected Empty - Environment as your current environment.
Step 2: Prepare your Job's Text for Text Parsing API
Starting with a Job Object (or any structured Job format), building a text similar to the original text of the Job is necessary before calling the Text Parsing endpoint. This task can be done by:
- merging description and their title with a single line jump
- joining sections with double line jumps
Here is an example with the Text Parsing results:
{
"name": "Data Scientist",
"url": "",
"summary": "Under general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.",
"location": {"text": null},
"archive": null,
"archived_at": null,
"updated_at": "2021-12-27T15:16:05+0000",
"created_at": "2020-12-24T09:32:11+0000",
"culture": "At our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.",
"benefits": "We offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.",
"responsibilities": "As a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.",
"requirements": "Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills",
"interviews": "During the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.",
"skills": [],
"languages": [],
"certifications": [],
"courses": [],
"tasks": [],
"tags": [],
"metadatas": [],
"ranges_float": [],
"ranges_date": []
}
Data Scientist
Under general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.
PhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field\nClinical Training or Experience\nLean & Six Sigma Training or Experience\nProject Management Training or Experience\nExperience in a Start-Up or Small Business Environment
At our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.
We offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.
As a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.
Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills
During the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.
Preferred
PhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field
Clinical Training or Experience
Lean & Six Sigma Training or Experience
Project Management Training or Experience
Experience in a Start-Up or Small Business Environment
{
"code": 200,
"message": "Text extraction finished in 0.20 seconds.",
"data": {
"entities": [
{
"end": 14,
"label": "job_title",
"start": 0
},
{
"end": 371,
"label": "task",
"start": 324
},
{
"end": 416,
"label": "task",
"start": 373
},
{
"end": 457,
"label": "task",
"start": 418
},
{
"end": 478,
"label": "skill_hard",
"start": 459
},
{
"end": 698,
"label": "education_title",
"start": 617
},
{
"end": 801,
"label": "course",
"start": 762
},
{
"end": 843,
"label": "course",
"start": 802
},
{
"end": 1189,
"label": "job_title",
"start": 1175
},
{
"end": 1467,
"label": "education_title",
"start": 1374
},
{
"end": 1586,
"label": "skill_hard",
"start": 1584
},
{
"end": 1599,
"label": "skill_hard",
"start": 1588
},
{
"end": 1604,
"label": "skill_hard",
"start": 1601
},
{
"end": 1620,
"label": "skill_hard",
"start": 1606
},
{
"end": 1681,
"label": "skill_hard",
"start": 1680
},
{
"end": 1689,
"label": "skill_hard",
"start": 1683
},
{
"end": 1700,
"label": "skill_hard",
"start": 1695
},
{
"end": 1789,
"label": "skill_hard",
"start": 1784
},
{
"end": 1798,
"label": "skill_hard",
"start": 1793
},
{
"end": 1847,
"label": "skill_hard",
"start": 1844
},
{
"end": 1955,
"label": "skill_soft",
"start": 1941
},
{
"end": 2221,
"label": "education_title",
"start": 2198
},
{
"end": 2279,
"label": "course",
"start": 2223
},
{
"end": 2292,
"label": "course",
"start": 2281
},
{
"end": 2342,
"label": "course",
"start": 2311
},
{
"end": 2382,
"label": "course",
"start": 2343
},
{
"end": 2424,
"label": "course",
"start": 2383
},
{
"end": 2479,
"label": "course",
"start": 2425
}
],
"parsing": {
"certifications": [],
"companies": [],
"courses": [
"Clinical Training or Experience",
"Computer Engineering, Industrial and Systems Engineering",
"Experience in a Start-Up or Small Business Environment",
"Lean & Six Sigma Training or Experience",
"Mathematics",
"Project Management Training or Experience"
],
"dates": [],
"durations": [],
"education_titles": [
"Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering",
"PhD in Computer Science",
"PhD in Computer Science, Computer Engineering, Industrial and Systems Engineering"
],
"emails": [],
"first_names": [],
"interests": [],
"job_titles": [
"Data Scientist"
],
"languages": [],
"last_names": [],
"locations": [],
"phones": [],
"schools": [],
"skills_hard": [
"Arena",
"Julia",
"NN",
"Naive Bayes",
"Python",
"R",
"Random Forests",
"SQL",
"SVM",
"Simio",
"predictive modeling"
],
"skills_soft": [
"Good scripting"
],
"tasks": [
"Responsible for applying data mining techniques",
"applying various machine-learning tools",
"statistical analysis of performance metrics"
]
},
"text": "Data Scientist\n\nUnder general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.\n\nPhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field\nClinical Training or Experience\nLean & Six Sigma Training or Experience\nProject Management Training or Experience\nExperience in a Start-Up or Small Business Environment\nAt our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.\nWe offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.\nAs a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.\nMaster's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills\nDuring the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.\n\nPreferred\nPhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field\nClinical Training or Experience\nLean & Six Sigma Training or Experience\nProject Management Training or Experience\nExperience in a Start-Up or Small Business Environment\n"
}
}
Text Parsing API
You can refer to Text Parsing to get more details about the Text Parsing API.
Step 3: Build your New Job Object
Using the results of the Parsing, we can enrich the initial Job Object by accumulating:
skills: append all entities of typeHardSkillandSoftSkilllanguages: append all entities of typeLanguagecertifications: append all entities of typeCertificationcourses: append all entities of typeCoursetasks: append all entities of typeTask
{
"name": "Data Scientist",
"url": "",
"summary": "Under general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.",
"location": {"text": null},
"archive": null,
"archived_at": null,
"updated_at": "2021-12-27T15:16:05+0000",
"created_at": "2020-12-24T09:32:11+0000",
"culture": "At our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.",
"benefits": "We offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.",
"responsibilities": "As a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.",
"requirements": "Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills",
"interviews": "During the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.",
"skills": [],
"languages": [],
"certifications": [],
"courses": [],
"tasks": [],
"tags": [],
"metadatas": [],
"ranges_float": [],
"ranges_date": []
}
{
"code": 200,
"message": "Text extraction finished in 0.20 seconds.",
"data": {
"entities": [
{
"end": 14,
"label": "job_title",
"start": 0
},
{
"end": 371,
"label": "task",
"start": 324
},
{
"end": 416,
"label": "task",
"start": 373
},
{
"end": 457,
"label": "task",
"start": 418
},
{
"end": 478,
"label": "skill_hard",
"start": 459
},
{
"end": 698,
"label": "education_title",
"start": 617
},
{
"end": 801,
"label": "course",
"start": 762
},
{
"end": 843,
"label": "course",
"start": 802
},
{
"end": 1189,
"label": "job_title",
"start": 1175
},
{
"end": 1467,
"label": "education_title",
"start": 1374
},
{
"end": 1586,
"label": "skill_hard",
"start": 1584
},
{
"end": 1599,
"label": "skill_hard",
"start": 1588
},
{
"end": 1604,
"label": "skill_hard",
"start": 1601
},
{
"end": 1620,
"label": "skill_hard",
"start": 1606
},
{
"end": 1681,
"label": "skill_hard",
"start": 1680
},
{
"end": 1689,
"label": "skill_hard",
"start": 1683
},
{
"end": 1700,
"label": "skill_hard",
"start": 1695
},
{
"end": 1789,
"label": "skill_hard",
"start": 1784
},
{
"end": 1798,
"label": "skill_hard",
"start": 1793
},
{
"end": 1847,
"label": "skill_hard",
"start": 1844
},
{
"end": 1955,
"label": "skill_soft",
"start": 1941
},
{
"end": 2221,
"label": "education_title",
"start": 2198
},
{
"end": 2279,
"label": "course",
"start": 2223
},
{
"end": 2292,
"label": "course",
"start": 2281
},
{
"end": 2342,
"label": "course",
"start": 2311
},
{
"end": 2382,
"label": "course",
"start": 2343
},
{
"end": 2424,
"label": "course",
"start": 2383
},
{
"end": 2479,
"label": "course",
"start": 2425
}
],
"parsing": {
"certifications": [],
"companies": [],
"courses": [
"Clinical Training or Experience",
"Computer Engineering, Industrial and Systems Engineering",
"Experience in a Start-Up or Small Business Environment",
"Lean & Six Sigma Training or Experience",
"Mathematics",
"Project Management Training or Experience"
],
"dates": [],
"durations": [],
"education_titles": [
"Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering",
"PhD in Computer Science",
"PhD in Computer Science, Computer Engineering, Industrial and Systems Engineering"
],
"emails": [],
"first_names": [],
"interests": [],
"job_titles": [
"Data Scientist"
],
"languages": [],
"last_names": [],
"locations": [],
"phones": [],
"schools": [],
"skills_hard": [
"Arena",
"Julia",
"NN",
"Naive Bayes",
"Python",
"R",
"Random Forests",
"SQL",
"SVM",
"Simio",
"predictive modeling"
],
"skills_soft": [
"Good scripting"
],
"tasks": [
"Responsible for applying data mining techniques",
"applying various machine-learning tools",
"statistical analysis of performance metrics"
]
},
"text": "Data Scientist\n\nUnder general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.\n\nPhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field\nClinical Training or Experience\nLean & Six Sigma Training or Experience\nProject Management Training or Experience\nExperience in a Start-Up or Small Business Environment\nAt our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.\nWe offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.\nAs a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.\nMaster's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills\nDuring the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.\n\nPreferred\nPhD in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field\nClinical Training or Experience\nLean & Six Sigma Training or Experience\nProject Management Training or Experience\nExperience in a Start-Up or Small Business Environment\n"
}
}
{
"name": "Data Scientist",
"url": "",
"summary": "Under general direction or assignment, develops high quality prediction systems integrated into existing systems and applications. Works collaboratively with a team utilizing industry knowledge, technology, data and statistical modeling to support fast-paced business decisions leading to improved outcomes. Responsible for applying data mining techniques, statistical analysis of performance metrics, applying various machine-learning tools, predictive modeling, and experimental design. Must be able to work independently on development and selection of machine learning techniques and algorithms.",
"location": {"text": null},
"archive": null,
"archived_at": null,
"updated_at": "2021-12-27T15:16:05+0000",
"created_at": "2020-12-24T09:32:11+0000",
"culture": "At our company, we foster a collaborative and innovative culture where employees are encouraged to explore new ideas and technologies.",
"benefits": "We offer competitive salaries, comprehensive health insurance, flexible work schedules, and opportunities for professional development.",
"responsibilities": "As a Data Scientist, you will be responsible for developing predictive systems, conducting statistical analysis, and applying machine learning techniques to drive business decisions and improve outcomes.",
"requirements": "Master's Degree in Computer Science, Computer Engineering, Industrial and Systems Engineering, Mathematics, or related field and\nExcellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.\nProficiency in common data science toolkits, such as R, Python, and Julia\nProficiency in data visualization tools\nProficiency in simulation software such as Simio or Arena\nProficiency in using query languages such as SQL\nGood applied statistics skills, such as distributions, statistical testing, regression, etc.\nGood scripting and programming skills",
"interviews": "During the interview process, we will assess your knowledge of machine learning techniques, your experience with data science toolkits, and your ability to apply statistical analysis in real-world scenarios.",
"skills": [
{
"name": "NN",
"value": null,
"type": "hard"
},
{
"name": "Naive Bayes",
"value": null,
"type": "hard"
},
{
"name": "SVM",
"value": null,
"type": "hard"
},
{
"name": "Random Forests",
"value": null,
"type": "hard"
},
{
"name": "Python",
"value": null,
"type": "hard"
},
{
"name": "Julia",
"value": null,
"type": "hard"
},
{
"name": "Simio or Arena",
"value": null,
"type": "hard"
},
{
"name": "SQL",
"value": null,
"type": "hard"
},
{
"name": "Good scripting",
"value": null,
"type": "soft"
}
],
"languages": [],
"certifications": [],
"courses": [
{
"name": "Clinical Training or Experience",
"value": null
},
{
"name": "Computer Engineering, Industrial and Systems Engineering",
"value": null
},
{
"name": "Experience in a Start-Up or Small Business Environment",
"value": null
},
{
"name": "Lean & Six Sigma Training or Experience",
"value": null
},
{
"name": "Mathematics",
"value": null
},
{
"name": "Project Management Training or Experience",
"value": null
}
],
"tasks": [
{
"name": "Responsible for applying data mining techniques",
"value": null
},
{
"name": "statistical analysis of performance metrics",
"value": null
},
{
"name": "applying various machine-learning tools",
"value": null
}
],
"tags": [],
"metadatas": [],
"ranges_float": [],
"ranges_date": []
}
Step 4: Index your Job
We can now Index the enriched Job Object:
Updated about 1 year ago
What’s Next