Job Boards Vs Job Search Engines online

With the advent of technology, many businesses and services have transformed and moved to the internet. The recruitment industry has also grown to a massive size in the last few years and today it far outpaces physical recruitment agencies. Online job boards and job search engines have brought job applications and job posts to the fingertips of people and anyone from anywhere can apply to jobs all over the globe today. Silkroad reports that in 2016, job boards and job search engines were the most commonly used hiring sources. While both of these are aimed at scouring for jobs for the modern job seeker, some prime differences are overlooked.


Job Boards

A job board is essentially a website where employers of one or more companies, post job vacancies, a digital alternative of the “Staff Wanted” sign. A job seeker searches through the job board for one that matches his qualifications then applies to any one of them. 

The job board acts as a mediator between the two groups- employers pay to post their jobs, and search for the right fit for their company; job seekers create a profile and post their resumes so they could be easily searched by prospective employers. 

There are two types of job boards:


Job Search Engine

A Job Search Engine or a Job Aggregator searches the web and finds job listings from job boards and company websites. While most charge employers to post job vacancies, others like Indeed let them do it for free only if they post the vacancy on their site and nowhere else. Job seekers, however, post their resumes online for free. 


There are three types of job search engines:

There are some employment websites that neither fit into the category of a job board nor of a job search engine. One example of such a site is LinkedIn– a confluence of both in certain regards. While it was built to be a networking site for professionals, it is common to find employers posting job vacancies on their LinkedIn company page. Glassdoor, meant to be an employer review site has evolved into a job posting website. An employer with good reviews garners many interested candidates. 


Job Boards vs. Job Search Engine

The clear demarcation between a job board and a job search engine is created by the fact that while a job board only shows postings of companies that came to them, a job search engine actively searches through thousands of listings to bring the ones that you wanted using an algorithm. 

However, the real differences are hidden in the way both operate. 



The pricing structure varies greatly between a job board and a job aggregator. The former sells job postings individually while the latter offers a job advertising model. While choosing a job site, you must be aware of the length of the contract. While some sites charge a fee for a job posting which then remains active for a set timeframe, others run on the “pay per click” model. You would have to pay for each candidate clicking on your post even if they do not apply, and it can run from anywhere between $0.10 to $5 per click. Thus, it depends on your choice- with a job board you enter into a contract for a specified period while with a job search engine.  



The search engines of both job boards and job aggregators function differently. A job aggregator uses bots to find new jobs across various websites and job boards and hence, show more results. Their search engine goes through everything- a job posting’s title, posting date, location and more. However, a job board looks only for job titles and location and brings up comparatively fewer results. So, if you are a candidate you may find the job search engine to be more suitable for your needs. 



Generally, a job aggregator brings in more prospective employees to the company as it shows more results as discussed above. However, visibility does not correspond to talent and more often than not, unqualified candidates show up for the job interviews. However, this does not happen with a job board and they focus on niche professions to bring in qualified people. 


It is worth noting that job boards bring in fewer hires but in this age of intense competition, why leave an opportunity? When seeking jobs it would be wise to use both a job board and a job search engine because that would ensure maximum outreach.

How to Create a Job Board using WordPress

In case you are looking to set up a business in the job domain, and want to build something using the latest tech available, a job directory site can work wonders. With the growing popularity of the gig economy and flourishing job opportunities in the major economies, both employers and prospective employees are turning to job boards to find the best fit for themselves. All you’d need is a website, and a data-source to make your business ready to take off.

The easiest way to do this, even if you’re from a non-coding world, would be with WordPress.

Necessary Features of a Job Board

While the layout of a job board can be customized according to your needs, some features are a necessary part of every job board.

Building a WordPress Job Board

Once you have these figured out, you will need to move on to the actual work of building the site. For that, you’d need:

You can also customize your site using plugins to increase site functionality, some of which are,

Data for Job Listings

Creating a well-designed job board will be redundant if you do not have a ready stream of job feed to populate your website and attract more customers. This is where JobsPikr comes in — it offers a wide range of data across different geographical locations and niches. So whether you want to build a job board only for data science or for construction-related jobs, we can help you. The data also gets updated every day so expired or old listings are absent in the feed. Several filters are available so that you can provide a better experience to your users.

You might think that integrating this data might be a headache, but that is not so with JobsPikr because you will be getting ready-to-use data in CSV or JSON format and this would help with easy integration. On top of that, you can choose to directly download the data or get it via Amazon S3, or FTP, dropbox or even REST APIs. Both maintaining the infrastructure and updating the system are things that are taken care of by us and all you need to do is focus on making your website look user-friendly and take care of the business.


Building a Job Board might seem to be a hectic task but with the help of WordPress and JobsPikr, it may prove to be simple enough that even a team of two can set it up and maintain it. While creating the website is a one-time task, it needs to be updated from time to time, using feedback from customers. On the data-front, any changes required in data or delivery methods can be communicated to our team and would be taken care of.

Download fresh job listings for your job board based on the exact search criteria for your niche with JobsPikr.

Job Data Analysis Reveals top Skills Required for Data Science Role

Data scientists help companies make solid data-backed decisions. It’ss also a relatively new career, residing at the intersection of social science, statistics, computer science and design fields. This job also happens to be the fastest growing job in the United States, according to LinkedIn. Data science job role has witnessed a growth of 6.5 times from 2012 and there are more than 6,000 data scientists jobs currently listed on LinkedIn. Apart from that Data Science job role also commands lucrative median salary of $113,000 among other fast-growing career paths.

While the job market continues to grow, the demand for data scientists directly results from the shortage of workers. As per a report by McKinsey, we might soon see a shortage of up to 250,000 data scientists. Hence, it would be very interesting to look at the type of skills that someone needs to master in order to become a data scientist.

The skills required for a data scientist are as follows. They must have good knowledge of data visualization and data processing. Cloud computing is a must and they must be flexible to work with different types of cloud-based systems. Understanding the problem and easy problem-solving solutions is a plus.

Since JobsPikr extracts job data from some of the popular job boards, we selected the job listings posted in March, 2018 on The next step involved segregating the job ads with job title as “Data Scientist”. Finally we got a data set of close to 8,000 job listings for data scientists in the US region.

In order to analyze the skills required for this role, we found out the terms present in the “job requirement” section of the job ad. Here is a sample job ad for better perspective:


Then, we moved to the count of terms of various skills and calculated the percentage of occurrence of these skills in the total number of job listings. Given below is the chart that shows the key skills found in the job ads for data scientists.


Let’s now go through these skills individually:


Python has amassed a lot of interest recently as a choice of language for data scientists. Here the factors that make it popular in the data science field:

For example, scikit-learnis used for machine learning algorithms, PyBrainfor building Neural Networks, matplotlibfor plotting and iPython notebooks to present the analyses.


Structured Query Language (SQL) is essential for data scientists as it is the standard language to communicate with relational database management systems (RDBMS). As a data scientist one has to write both both simple and complex queries to select data from tables apart from understanding of different data formats for data management and filtering.


R is a powerful language developed in the early 90’s; currently it is used widely for data science, analysis and statistical computing. Its popularity can be largely attributed to the following:


Since Java is a very old programming language and popular among data scientists in the operational analytics space. It is quite evident that many enterprises already have systems developed with this language. Hence, the models are written in Java as it will be easier to integrate. Apart from that leading Big Data frameworks/tools like Spark, Hive, and Hadoop are written in Java. It is also a great choice when it comes to scalability and speed.


As a framework Hadoop has gained massive popularity and has become the de facto open source software for reliable, scalable, distributed computing involving big data analytics.


This tool is a leader in the commercial analytics space. It has a huge set of in-built statistical functions, good UI (Enterprise Guide & Miner) for any user to quickly learn and delivers superior technical support. However, it is expensive and its certification programs can also cost a lot.


Apache Spark is open source and it has the ability to keep data resident in memory, which can lead to faster iterative machine learning workloads. In addition to this, what makes it adoption stronger in data science community is its base on Scala and in-built machine-learning library, MLlib.


Similar to Java, C/C++ is also used write models and it is critical for writing the algorithmic extensions for R and Python.


Any data scientist looking to work on large data sets in a JVM-centric stack will be using Scala. Many of the high performance data science frameworks are written using Scala owing to its amazing concurrency support.


Unlike SQL, NoSQL offers an architectural approach with lesser constraints. In general, it is easier to break down NoSQL data stores, but more complicated to query them for complex results.

For data scientists, NoSQL can be somewhat tricky — although the technology makes it absolutely easy to rapidly accumulate massive data sets and rapidly scale data stores to meet demand, it requires de-normalization of data.


VizQL (Visual Query Language) is Tableau’s database visualization language which queries relational databases, cubes, cloud databases, and spreadsheets, and then generates wide range of graphs and chart. These graphs can be combined into dashboards and shared via web. This application is particular useful for data exploration and interactive analysis.


Although MATLAB is not as popular as R or Python in the data science space, it still has a lot of traction in the academia. Also, it is a commercial app with high cost and good customer support.


This is a popular data warehouse software in the Hadoop ecosystem that helps data scientists in data transformation and analysis. It provides an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.


Microsoft Excel can be considered as a bridge application for very quick filtering and data analysis using in-built statistical methods. However, it becomes powerful when combined with Visual Basic. Check out the examples for building your own Excel-based neural network and Monte Carlo simulations.


Apache Cassandra is an open source distributed NoSQL database management system designed to handle large amounts of data across many commodity servers. As this database was developed for Facebook, where millions of reads and writes happen at each given second, its performance is far superior.


It is a programming model that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. Simply going by the name, MapReduce consists of two steps: Mapping and Reducing the data:


This is the open source framework developed by Google Brain Team for machine learning and deep neural networks research. Definitely aspiring data scientists looking to work on neural networks must give preference this framework.


It is a high level scripting language used for operating on large data sets inside Hadoop. It primarily used to apply schema and transform data.


This sums up the overview of the important skills a data scientist must acquire for better opportunities in career. If you would add any other skill or the reason behind learning a particular skill, do share with us via comments.

Acquire clean and up-to-date job listings data in a structured format via JobsPikr.

Interesting Insights from Job Board Data Analyses

Revenues for the online recruitment vertical have grown at an average rate of 14.6% over the past five years, according to the research firm IbisWorld. And the momentum isn’t expected to stop: The industry made $4.4 billion in 2017 and is anticipated to rake in $6.4 billion in 2022 according to the same business intelligence company.

Unemployment is near record lows, leaving companies struggling to find the right talent. Wages are also finally increasing which is making it difficult to lure people away from current jobs. Considering this, the job boards are in sweet spot right now; however, the market is getting crowded by new entrants trying to get a piece of pie. This essentially means job boards need to concentrate on getting high quality job listings in order to cater to the rising demand.

In this post we’ll cover some of the compelling insights that we unveiled by analyzing the job data feed delivered by JobsPikr — a platform to access fresh job posts from company sites and job boards.


This dataset is comprised of data extracted from some of the popular US-based job boards such as CareerBuilder, Dice, Monster and Indeed. The total record count was more than 150,000 for the job postings crawled in the last 30 days. Given below are the data fields:

Note that all the job boards won’t have above-mentioned data fields — it varies depending on the portal.

Exploratory analyses

We’ll perform exploratory analyses on the vital data fields to understand the present state of the job market. Then, we’ll move to text mining of job requirements and descriptions.

Top job categories

Given below is the chart depicting the top job categories — we can see that ‘sales’, ‘engineering’, ‘marketing’ have captured the top three spots.

Job categories

Top locations in terms of job postings

Here we’ll uncover the top 10 locations in the United States with most number of job openings. The chart shows that ‘Atlanta’, ‘San Francisco’ and ‘New York City’ feature as the top three cities in this case.

job locations

Top companies with job listings

Let’s now find out the companies that have listed job openings. We can see that the leading recruitment and employment agencies like ‘CyberCoders’, ‘Robert Half’, ‘REED’ and ‘Hays’ have captured a major share. Deloitte as a service network company has got the third spot.

top companies

Top job titles

Let’s now analyse the job titles to figure the most in-demand positions. We can see can that cumulatively there is substantial demand for managerial positions cutting across all other job roles. Other than that engineering and development related roles have significant openings. Next up are the sales and consulting roles. The chart also shows that ‘Java’ and ‘SAP’ related job titles are in demand as well.

Top terms in job titles

Salary range

The predominant salary range falls in between $80k to $120k. Other salary ranges that are more than 300k and go up to $500k are outliers.

Salary histogram united states

Job type

We can see that majority of the job openings are on ‘full time’ basis and ‘temporary’ jobs are least in number.

job type

Text mining

Now we’ll perform text mining techniques to on the job description and job requirements fields to understand the top terms used to describe the job and the associated skills.

Top terms in job description

Let’s find out the most frequently used words in the job description using the word cloud given below:

wordcloud-job description-us

We can see that ‘Experience’ is the most frequently used word in job description. Other words with higher frequency are ‘work’, ‘years’, ‘team’, ‘skills’.

Top skills

Now let’s uncover the most in-demand skills by going through the job requirements posted in the job listings. Here is the word cloud created using the frequency of occurrence of the term.

wordcloud-job requirement

Clearly degree, diploma and certification are most common and predominant elements in the job requirements in terms of education. Further analyses of the word frequency reveals the following top 10 skills:

It is quite evident that older technologies like Java and C are still in demand. Apart from that, skills around data analysis and security are also sought after.


In this study, we analyzed the clean job feeds delivered by JobsPikr to understand the current US job market. Apart from exploratory analyses, other advanced techniques such as topic modeling can also be applied for better job matching in job boards.

Let us know in the comments section if you would like to uncover any additional insight.

Acquire clean and up-to-date job listings data in a structured format via JobsPikr.

Crawling Job Boards vs Crawling Company Careers Pages

If you are connected to the recruitment industry in some way, you wouldn’t need an introduction  to the value of job listings as one of the key market growth indicators of this industry. Recruiters, HR consultancies and labor analytics firms would find job data to be resourceful in planning, analyses and market research among many other applications.

Candidates mostly rely on job boards to find new and relevant job opportunities. Job boards do a great job in connecting employers and candidates. The job listings found on these job boards are published by the companies themselves or other third party agencies. Posting the listing on a job board is typically the second step after the company posts it on their own career page in the website.

When it comes to extracting job data, we have to make a choice between the job boards and company career pages as the sources. Here’s a comparison of the two, which will be helpful if you are evaluating both these options to get job feeds.

How job boards work

There are hundreds of thousands of job boards out there, each catering to a different industry/niche and working on various business models. Companies choose a few job boards that are relevant to their industry while posting the jobs. The job board charges the company a fee in return for the job listing, which is the primary revenue model of most job boards. Sometimes, companies also accept job applications directly through the job boards and this makes it easy for the candidates to apply for different jobs without actually going to the company pages.

The job board essentially has a pool of candidates who are looking for new opportunities and this is what employers get access to by posting a job. Indeed is one of the leading job boards with listings across a broad range of industries.

However, not all companies post jobs in generic job boards like Indeed; many companies post their jobs on some other niche job boards. This is where it gets confusing, should you crawl a set of known job boards or crawl the company careers pages instead?

Crawling company pages vs crawling job boards

As we discussed earlier, the company careers page is almost always the first place where a new job opening is posted. By crawling these pages, you can be the first person to get the job feeds before it even reaches the masses through various job boards. Extracting job listings directly from the company pages is the ideal option if you are concerned about the data quality. Here is a comparison of crawling company careers vs crawling job boards, on the basis of different aspects of job data.

Comprehensiveness of the data

It’s a no-brainer that the comprehensiveness of the data would be very high when you get it directly from the company’s own page. Since different job boards have different job listing formats, they may not have all the information as the original company page posting. Sometimes, the job postings on the job boards are not directly posted by the companies, but by agencies on behalf of the companies. This again increases the chance of inaccuracies in the job posting data found on job board websites. If your job data use case demands comprehensiveness, it’s recommended to get the data directly from the company pages.

Reliability of the data

Often, the data available on job boards is found to be redundant and unreliable. The job postings on job boards would become redundant if the company fails to take down the listing once the position has been filled. This is in fact a common scenario. If you are crawling just the job boards, you may end up with data that holds no relevance in the present time and weeding them out would easily become a task in itself.

To make things worse, some new job boards try to promote themselves by posting duplicate jobs on popular job boards, linking back to their website. Scraping this data is not only unnecessary but can easily cause confusion and also ruin the quality of your job feeds.

On the other hand, the company careers pages are typically always up to date and wouldn’t have redundant listings. You can always be sure about the relevancy of the data when you’re crawling the company pages.

Speed of access

If your job data use case is time-sensitive, look no further than crawling the company careers page as this is where all the new job listings get posted first. This is especially important if you’re a staffing agency looking to generate leads by staying up to date with the new jobs being posted in the region you’re targeting. By crawling the company careers pages, you’ll be sure to know about the new opportunities before your competitors, essentially improving your bottom lines.

How easy is it to crawl hundreds of company pages?

You might be wondering how crawling a huge number of company pages might even be feasible in the first place. This is indeed a valid concern. It’s definitely not easy to set up crawlers for each company site from which you need job feeds.

This is exactly why we leveraged our domain knowledge in crawling along with  machine learning techniques to build JobsPikr, a solution that can intelligently identify and extract relevant data points from the careers pages of company websites.

With JobsPikr, getting job data from job boards as well as thousands of company pages is as easy as picking the sites you want and hitting ‘Subscribe’.

Acquire clean and up-to-date job listings data in a structured format via JobsPikr.