Web Scraping Job Postings: A Guide For 2024

Companies need job listings data to evaluate their recruitment strategies, analyze trends in the labor market and compare their practices to those of their industry peers. With more data about jobs getting posted on various platforms regularly, companies need effective methods of scraping the data.

This article is about the most effective methods you can use to scrape job posting data in 2024. Python, one of the most common scripting languages, had inbuilt web scraping libraries, is commonly used to build web scrapers. However, one can decide to use the programming langauge to build a scraper in-house, purchase a prebuilt tool or obtain pre-scraped data. We evaluate all the possible options and explain in detail what can work best for you in 2024.

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Why is Job Board Scraping Difficult?

know more about job listing scraping

Anyone who has ever attempted to scrape jobs online appreciates the difficulties involved in the process. Job listing boards deliberately prohibit bots from crawling their sites to collect data about jobs. Some websites even state their anti-scraping policies in their terms of service. These websites use various anti-scraping tools to achieve this objective. Some of the most common and effective tools include Completely Automated Public Turing tests (CAPTCHAs), complex JavaScript evaluation, and the use of dynamic content.

Anti-Scraping Techniques

Anti-scraping tools function simply. First, they must detect attempts to crawl websites. The tools do this by evaluating IP addresses, browser parameters, and the general behavior of requests. Once they determine that the request does not meet their criteria, the bots block access, thus preventing scraping. Website owners using these tools can adjust the way they function to suit their demands. Some websites utilize CAPTCHAs and avoid JavaScript techniques.

Other job posting websites also use legal methods to block scraping attempts. Such sites deliberately state in their terms and conditions of service that they do not allow any other party to scrape data from their databases. You may have to obtain express consent to scrape data from such platforms.

The use of dynamic content, CAPTCHAs, and IP blocking techniques can effectively prevent data scraping. You need advanced scraping tools and techniques to successfully obtain data from websites that use dynamic content and other common anti-scraping tools.

Overcoming Anti-Scraping Techniques

Web scraping job technologies keep evolving. These changes are in response to the use of anti-scraping tools that websites use. Thus, many techniques for bypassing anti-scraping techniques used by job boards are available.

For example, those seeking data from job boards can now bypass IP reputation checks. One of the techniques involves delaying the speed of the web scraping tool. The job scraper then sends requests to the server at intervals, thus mimicking human activity. The IP-checking tool permits such requests.

You can also use headless browsers to scrape data from websites that use dynamic content and CAPTCHAs. Such headless browsers or APIs overcome the use of dynamic content to block scraping quite effectively.

Furthermore, the use of headless websites and ISP proxy can help you bypass the JavaScript anti-scraping technique. The JavaScript challenge works by checking the IP request for a few seconds before proceeding to either block or permit it.

It is also easy to overcome the ability of some websites to analyze the general behavior of requests by using rotating proxy servers. The proxy servers distribute the requests to the servers of the website across multiple IP addresses. Thus, this method helps to bypass the ability of anti-scraping tools to analyze IP address behavior and deny them access.

However, the competition between web scraping and anti-scraping techniques will continue for a long time. Therefore, you need to keep abreast of developments to complete job board scraping projects without being identified and blocked by anti-scraping tools.

Compliance

Whether you are using prebuilt job scraping tools or a scrape job tool developed in-house, you should adhere to standards and best practices for scraping the data. Many websites include the issue of data scraping in their terms of use. Here are some of the things you can do to ensure your job-scraping project is ethical and done within the law.

For example, it is important to use the scraped data for its intended purpose. If your company needs to scrape job data from relevant websites to understand current trends in the job market, it should ensure the scraped data is used for this purpose. Some firms need the job listing information to evaluate their competitors’ performance. In that case, the firms should ensure the data is used solely for this purpose.

Methods of Web Scraping Jobs

Web scraping jobs online may be a complex process, depending on the method you decide to use. There are three main methods of scraping data on jobs from relevant websites. Let us look at these methods in detail.

Buying a Prebuilt Job Scraper

A prebuilt job scraper enables you to crawl relevant websites and extract job listing data without being detected or blocked. Various companies and developers create and market job scraper tools. Furthermore, this option is ideal for developers who understand how the tools work and can use them comfortably.

How to buy a prebuilt job scraper 

When buying a prebuilt scraper for job listings, you need to get the best that suits your needs. But how do you select the right scraping tool from a market full of alternatives? Here is a breakdown of getting the best-prebuilt job scraper.

  1. Research
  2. First, you need to familiarize yourself with the different prebuilt scrapers available on the market. You can do this by following authoritative blogs on the topic. Your research should be guided by your objective of getting a prebuilt scraper. In this case, you need a scraping tool you can use to extract job data from selected websites. Research helps you to narrow down the search to a handful of alternative tools available.
  3. Evaluate alternatives
  4. It may be difficult to settle on one brand of prebuilt scraper because all prebuilt scrapers have the same standard features. However, every prebuilt scraper has its uniqueness in terms of many factors. Use these differences to evaluate your options before settling on one.
  5. For example, consider the ease of use when choosing a tool. Some prebuilt web scraping tools have great interfaces. Such a feature makes the use of the tools easy for everyone.
  6. Performance is another important feature to consider when evaluating the tools. The best tools are scalable; therefore, you can adapt them to the size of the scrape job project.
  7. Other features to consider when evaluating job scraping tools include versatility and storage. Some tools are suitable for handling data in various formats. Besides, they can be used on static and dynamic websites. More so, the best tools have massive data storage capacities to enable you to handle huge scraper job endeavors.
  8. Signing up

Some vendors of prebuilt scrapers give their clients trial offers. Such offers vary in terms of the period and the number of features one can access during the trial time. Trial periods are perfect for those who are not conversant with using advanced features of such tools. You can take advantage of the period to have a feel of all the features of the site before buying it. Alternatively, proceed to make the full purchase if you are certain that the tool will serve the intended purpose.

All prebuilt scraping tools come with API documentation. You will find detailed information on how to use the tool here.

Advantages of a prebuilt scraper 

One of the main benefits of using a prebuilt scraper is the convenience of using it straightaway. These tools provide an out-of-the-box solution to anyone who would like to carry out a scraping project of any size. Thus, opting for a prebuilt tool saves you a lot of development time.

The second benefit of using this option is support. Companies selling prebuilt tools offer customer support services. You can reach out to them for technical assistance whenever you need it.

Third, prebuilt tools come with anti-scraping tools. You can use the APIs to bypass some of the most common anti-scraping techniques websites use like advanced JavaScript tests and CAPTCHAs.

Disadvantages of using a prebuilt scraper 

The main downside of using a prebuilt scraper to scrape jobs online relates to control. If you build an in-house scraper, you will have full control over the code and the entire development process. However, buying a prebuilt scraper means that you do not have such a level of control even though you can expand the functionality of the tool.

Buying a Job Listing Database

Some companies use their built-in job scrapers to obtain data on job postings available online. The companies use their job scraping tools to obtain the data and then sell it to any interested party. These service providers identify websites with the most valuable and relevant data for scraping. Some of these websites include career pages of companies, major websites that publish job openings, professional networking sites, and niche job portals specific to certain industries. They extract the data, clean, it, and provide it for sale online.

Benefits of buying job listing databases 

Your business can benefit in many ways from purchasing pre-scraped job data from vendors. The first benefit relates to the ease of obtaining the data. You do not have to spend a lot of money and time running a development and testing program in-house to get a scraper.

More so, you do not need to invest in expertise to use and maintain a pre-built scraper to get job data. Your team can start using the data immediately after buying it from a vendor.

Third, the cost of obtaining pre-scraped job listing data is much less than that of building an in-house scraping tool or even purchasing a pre-developed one. Small companies keen on cutting operational costs can find the option of purchasing job databases more appealing than the other two options.

Disadvantages of buying Job listing databases 

The main disadvantage of purchasing a job listing database is that you do not have control over the data acquisition process. The developers of the database may have obtained the data unethically or illegally. However, using an in-house or prebuilt tool gives you full control of the process of scraping websites for job data.

Furthermore, pre-scraped databases may contain outdated data. Using such data may not provide accurate and reliable answers to your business problems.

Building a Job Scraper

building a job scraper

Building a job scraper is a viable alternative if you have the time and resources for the project. Developing job scraping tools requires heavy investment in terms of human effort, technologies, and financial resources. Furthermore, you need to put in place the right measures to ensure the development, testing, and final deployment of the job scraper is successful.

It is important to answer a few important questions before starting to build a job web scraper. First, consider the data storage needs of the project and what you can access. Data storage is a very critical issue when developing a web scraping tool. It is common for companies investing in the process to invest in data storage and saving solutions. Luckily, there are many such commercial solutions available on the market.

Second, you should consider the quality of the testing environment you will use for the tool. A stable and reliable testing environment helps you to meet all the specifications of the tool. The development team will use the testing environment to evaluate every aspect of the tool. The team will spot any problems and fix them during the testing process. Therefore, a good testing environment facilitates iteration.

How to Build a Web Scraper 

Building a job scraper from scratch is a long and tedious process. Here is a breakdown of the process.

  1. Decide on the language to use
  2. Developers often use Python to write the code for scraping data from websites. However, you can choose any applicable language you are comfortable using to complete the job. Besides, the steps of scraping job listing data from websites are the same despite the language one uses.
  3. Prepare the coding environment
  4. Preparing your coding environment entails two things. The first one is to download and install the language you intend to use for the project. If it is Python, then proceed to download the program and set it up on your device if you do not have one already installed. The second step at this stage involves setting up the right integrated development environment. There are tens of IDEs to choose from.
  5. Inspect data on the website
  6. Navigate to the website that contains job listing data that interests you. Inspect the data to notice the relevant HTML patterns on the website. This step is necessary for writing the code to use to finally extract the data.
  7. Scrape the data
  8. This stage entails the actual extraction of the data. The size of the data you intend to scrape determines the techniques you use at this stage. However, the process involves using a headless browser to send a request to the selected website, parsing the HTML file, and then storing all the data in a file format.

It is a good practice to fetch as much data as possible from the website you are interested in during this process. Collect all the data from the JSON file of your resource. The data contained in the JSON-formatted file contains additional points. Such data points are not available in the HTML file.

Benefits of building a scraper tool

You need to invest time and money to successfully scrape jobs online using an in-house tool. However, there are many advantages of building a scraping tool instead of using a prebuilt one or buying jobs databases.

Building a scraping tool gives you absolute control over its functionality. The developers’ team can quickly identify and fix any fault in the way the API functions. Furthermore, total control over the scraping tool means that you can customize it to your organization’s needs.

It is difficult to customize the functioning of a prebuilt scraping tool to the needs of your organization. Similarly, you may have to bear with the way such a tool works even when it does not suit all your business needs.

Disadvantages of building an in-house web scraper 

The disadvantages of building an in-house web scraper are obvious. You need a considerable investment to complete such a project. Your company will have to build and maintain a team of developers to manage the process and keep the API functional. This requirement contrasts sharply with the need to purchase either a pre-built scraper or a job listing database. For these two options, you simply invest in obtaining a prebuilt tool or buying the data and using it straight away.

The second disadvantage relates to the time it takes to develop and test such a tool. Companies have to make business decisions based on the timeframes of developing the scraper.

Job Scraping using Proxies

job scraping using proxy

Job scraping using proxies gives you an extra layer of security and help. Using proxies to complement your job-scraping tools enables you to complete large scraper jobs quickly and safely. Here at Rayobyte, we have four types of proxies to choose from residential, ISP, data center, and mobile. Although all these proxies are some of the most reliable ones in the world in terms of helping you avoid blocks and bans, they are not all perfect for scraping jobs. Therefore, you should choose the right proxy from our offerings for your scrape job.

There are many benefits of using proxies to scrape jobs online. The main one is about protecting your IP address when scraping websites for job data. Most websites interpret requests from bots or APIs as attack attempts. The inbuilt anti-scraping mechanism switches into action and blocks the IP addresses sending requests to the websites.

A proxy helps you overcome the main challenge of scraping data from websites. A good proxy, like the Rayobyte residential proxies or the Rayobyte data center proxies, hides your real IP address when you visit websites to scrape data. The website you are interested in registers the IP address of the proxy. So, if the website blocks the proxy IP address, you can switch to another and continue with your research.

It is important to consider the following issues when using proxies with scraper jobs tools. For example, you need to decide whether to use static or rotating proxies. Static proxies do not change over time or when the website you are visiting blocks them. These types of proxies act as your residential address.

Rotating residential proxies are different from static residential proxies because of their ability to change. Rotating proxies appear like your home addresses; however, they keep changing automatically to avoid getting blocked. In other words, using a rotating residential proxy is like having multiple home addresses and utilizing them all at once.

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Final Thoughts on Web Scraping Job Postings

conclusion on job scraping with proxy

All three main ways of web scraping job postings discussed in this article are effective. You can use either a prebuilt scraper or one built in-house to scrape vital data about jobs from selected websites. It is also convenient to purchase such data that has already been extracted, cleaned, and stored in a CSV file format. However, your decision on which method to use depends on many factors your business needs, the amount of money you are willing to spend, and whether you have an in-house technical team.

Building a job scraper in-house gives you absolute control over the process. You can customize the tool to your needs and apply it to other large projects in the future. A prebuilt tool gives you the convenience of launching the scraping project immediately. Check the Rayobyte range of residential proxies with the backing of real ISPs to give you the safety and convenience you need for large projects.

The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.

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