ResuMe: your online job-matching tool

30 June 2020 Updated at 30 June 2020

Currently, many people are reconsidering their career choices and look for new horizons. In the IT sector, there are various job profiles and vacancies. However, many still look alike. Therefore, I will show how ResuMe, your online personal job-matching tool, helps you to match your CV with relevant job profiles and vacancies at Business & Decision, by example. It gives you an exciting insight into what might be your future job.

ResuMe: your online job-matching tool

What is ResuMe?

ResuMe is an automated CV parser, an online job-matching tool. It extracts and visualizes what is unique about your CV. Besides, the application also identifies your skills. It uses those, together with your work experience, education, and achievements, to match your profile.

For example, at Business & Decision Belgium, we have nine job profiles and related vacancies. The ResuMe tool calculates your match percentage and provides you a detailed overview of your correlation with each job profile. That overview includes a comparison of your skills with the top 20 skills of our consultants in a specific job profile.

It helps you to identify fast which of your skills already match and which you still have to acquire. ResuMe also shows you exciting customer references where our consultants with your skills and job profile worked on. When you match with, e.g., our Web & Mobile profile, you get insight into the reference case of our customer Rive Gauche, a shopping center in Wallonia. Last but not least, ResuMe matches you with the vacancies that best fit your CV.

Example of word-cloud and matching profiles from ResuMe application
Example of word-cloud and matching profiles from ResuMe application

How does ResuMe work? 

ResuMe is available on the Belgium Business & Decision website. You can easily use it by the following three steps:

   1. Upload your CV

   2. Run the tool

   3. Check your match(es) and highlights

When uploading your CV in Word- or PDF format to the platform, the back-end of the ResuMe application selects your CV’s valuable terms. It converts these into a numeric format as input for the matching algorithm. Additionally, the app sends the resulting world-cloud and matching job profiles to the ResuMe front-end so that you can view it. 

Right now, ResuMe is in use as online job-matching tool by recruiters. It lets them quickly start a conversation with you based on your world-cloud and matching job profiles. For instance, a job seeker with a Ph.D. completed in Norway uploaded her CV, and the word-cloud mentioned the term Ph.D. and Norway. Our recruiter used this to open the conversation and invited the job applicant to share her experiences.

Besides, the recruiter also discussed the matching with the company ‘data scientist’ job profile, generated by ResuMe. Furthermore, by presenting some projects, the job applicant got an insight into the day-to-day tasks and the applicable career growth path. 

What technology uses ResuMe?

The back-end development of the ResuMe application took place in python. We used different Natural Language Processing (NLP) libraries to perform a set of six tasks:

Task 1: Extract the text from the CV.

Task 2: Split the text into separate words or tokens with a tokenizer.

Task 3: Remove stop words (i.e., words that don’t contain meaningful information, such as ‘the,’ and ‘a’).

Task 4: Use lemmatization to reduce inflectional word forms to a common base form. For example, reducing the words ‘organizes’ and ‘organizing’ to ‘organize’.

Task 5: Generate n-grams for words that often appear together. For instance, when you see “data science,” it makes more sense to treat these words as one token ‘data_science’, instead of two tokens’ data’ and ‘science’.

Task 6: Transform the tokens into numerical values using the tf-idf technique. This technique assigns a higher weight to unique words that often occur in a particular document, but not in the other materials. 

We are now ready to insert the numerical values in a machine learning model to start the matching process.

Deployment

To deploy the application, we used a containerized, micro-services approach. It means that you have multiple small virtual containers. Each has a specific task, and all virtual containers mutually communicate.

Additionally, a python flask API serves as back-end and handles the requests of a react-js front-end. We link it through an nginx reverse proxy container and make use of a mongo-db database to save the results. Last but not least, everything is put into the cloud using Azure web apps.

Resume: a new online job-matching tool

Are you curious to use ResuMe as your online job-matching tool? Well, the good news is that you can! It is freely available on our website. So, if you are looking for a career switch or a new challenge, try it and experience the added value it generates for you.

Find your matched profile(s), get insight into acquired- versus needed skills, learn about fascinating real-life customer cases, and discover your next job offer. 

Desiree Timmermans
Desiree Timmermans Business Owner
HelpToGrowBusiness

After a 15+ year career in IT, I felt in 2017 that it was time to follow my entrepreneurial spirit and help businesses embrace the digital world’s opportunities. I now run a unique sales and marketing agency focusing on helping ICT companies grow faster. My…

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