
Job Description Chrome extension
Challenge
I work in the Upstaff team, where we develop both turnkey projects and help expand the existing team (StartUps, SMBs, and engineering departments of large corporations). Everyone at some point lacks expertise and wants to attract simple. Like, say, call a taxi. My clients want to be able to scale very quickly and do not want to spend the standard 1-2 months on finding talent, which is a standard time to hire metrics in the IT industry.
We had three main challenges for which we needed help constantly:
- Be able to analyze an IT vacancy fast (especially a large one with several pages), sort everything out
- Create recommendations on things to improve in your vacancy to attract the attention of the right specialists as quickly and fully as possible. These are our checklists, proven over the years, and other tools, such as some AI assistance.
- Get profiles of several developers at hand that fit there to the maximum extent.
Tech Challenges
- Performance
The first thing we encountered (including on the example of similar extensions). Most of the extensions that analyze the content of the page and make changes (for example, highlight elements) begin to make themselves known and slow down the browser by increasing the number of tabs where the extension works. - Display Options
We played with drop-down windows but stopped at the sidebar because the windows constantly close when you go to another page or just a careless click. - Web resource coverage & support
We proceeded from the reasoning that 90% of recruiters use similar platforms for posting JOBS (Indeed, Glassdoor, Linkedin Jobs, Workable, JobLeads), and we implemented support for these platforms first. Abstract parser of abstract pages, where content may occur – the plugin may not correctly highlight technical terms, or find elements. We are considering supporting Google Docs (as an interim option for preparing a JOB description), but for now, we have stopped at the platforms themselves. - Text analyses and context
The context of parts of words in a sentence, for example, the programming language Go / Golang. People often use the verb go not at all as the name of a programming language, or the official library next (next.js).
I work in the Upstaff team, where we develop both turnkey projects and help expand the existing team (StartUps, SMBs, and engineering departments of large corporations). Everyone at some point lacks expertise and wants to attract simple. Like, say, call a taxi. My clients want to be able to scale very quickly and do not want to spend the standard 1-2 months on finding talent, which is a standard time to hire metrics in the IT industry.
We had three main challenges for which we needed help constantly:
- Be able to analyze an IT vacancy fast (especially a large one with several pages), sort everything out
- Create recommendations on things to improve in your vacancy to attract the attention of the right specialists as quickly and fully as possible. These are our checklists, proven over the years, and other tools, such as some AI assistance.
- Get profiles of several developers at hand that fit there to the maximum extent.
Tech Challenges
- Performance
The first thing we encountered (including on the example of similar extensions). Most of the extensions that analyze the content of the page and make changes (for example, highlight elements) begin to make themselves known and slow down the browser by increasing the number of tabs where the extension works. - Display Options
We played with drop-down windows but stopped at the sidebar because the windows constantly close when you go to another page or just a careless click. - Web resource coverage & support
We proceeded from the reasoning that 90% of recruiters use similar platforms for posting JOBS (Indeed, Glassdoor, Linkedin Jobs, Workable, JobLeads), and we implemented support for these platforms first. Abstract parser of abstract pages, where content may occur – the plugin may not correctly highlight technical terms, or find elements. We are considering supporting Google Docs (as an interim option for preparing a JOB description), but for now, we have stopped at the platforms themselves. - Text analyses and context
The context of parts of words in a sentence, for example, the programming language Go / Golang. People often use the verb go not at all as the name of a programming language, or the official library next (next.js).
Solution
Core Features Overview
As soon as users enter one of the popular platforms such as Linkedin, Indeed, Glassdoor, or Upstaff, you get an X-ray in terms of technical requirements: programming languages, frameworks, libraries, utilities, small tools – all this is highlighted on your page.
In the sidebar, you will receive this information in a structured form, grouped by categories. For each name, you have indicators of popularity in the industry, and how much this term is disclosed in the job description. Thus, we have indirect information that the author of the Job Description considers more important, and how much this correlates with the general “temperature in the hospital” / industry.
Users also get an assessment of whether enough technical terms are used in the job description.
In the next block, you will see suggestions for using technical terms. For an IT specialist, it is important to get a description of their own system of coordinates and terminology. We also take into account frequent misspellings, abbreviations, and long names and offer alternative options if they are more familiar to developers.
At the top, you see the overall Job Description Score. The goal is to achieve the maximum score. This means that within the scope of the job description, the work is done, and now you can proceed to posting on other resources and ATS.
Core Features Overview
As soon as users enter one of the popular platforms such as Linkedin, Indeed, Glassdoor, or Upstaff, you get an X-ray in terms of technical requirements: programming languages, frameworks, libraries, utilities, small tools – all this is highlighted on your page.
In the sidebar, you will receive this information in a structured form, grouped by categories. For each name, you have indicators of popularity in the industry, and how much this term is disclosed in the job description. Thus, we have indirect information that the author of the Job Description considers more important, and how much this correlates with the general “temperature in the hospital” / industry.
Users also get an assessment of whether enough technical terms are used in the job description.
In the next block, you will see suggestions for using technical terms. For an IT specialist, it is important to get a description of their own system of coordinates and terminology. We also take into account frequent misspellings, abbreviations, and long names and offer alternative options if they are more familiar to developers.
At the top, you see the overall Job Description Score. The goal is to achieve the maximum score. This means that within the scope of the job description, the work is done, and now you can proceed to posting on other resources and ATS.
Results
- Our managers at Upstaff use it daily for routine tasks such as analyzing third-party job descriptions, or improving JD of vacancies they are working at the moment.
- 85% satisfaction rate., +10% increase in efficiency
- Chrome extension up and running, attracting new users with % prospect->client conversion
- Our managers at Upstaff use it daily for routine tasks such as analyzing third-party job descriptions, or improving JD of vacancies they are working at the moment.
- 85% satisfaction rate., +10% increase in efficiency
- Chrome extension up and running, attracting new users with % prospect->client conversion