Mauka Jobs: Submission for Marshall Wace Philantrop{Hack} x Hex Cambridge 2021


As a result of the COVID-19 pandemic, it is estimated that the unemployment rate in the world has massively risen especially in developing nations. Additionally, after researching solutions that assist in finding job opportunities catering to users in developing nations, we found some current solutions to be confusing to navigate. With this rising problem in mind, our team was hoping to devise a solution to assist the unemployed in developing countries through Mauka. To help that have lost their job, we decided to only have those roles which were entry level, so that people could use the resources to learn on their own time, and then apply to that specific role.

What it does

Mauka, meaning opportunity in Hindi, is a user-friendly web application for users in developing nations to learn more about job opportunities around them. Once a user enters their city in the main search bar, they will be directed to a webpage where they can see the job roles with their corresponding job openings and average salary. Mauka also offers a simple “Demand” bar which displays how sought-after a job role is. If a user is appealed by the job role, Mauka allows them to explore more details about the role such as valuable interview preparation resources and a concise breakdown of which companies are recruiting candidates for such a role.

How we built it

Mauka was built using a Kaggle data set containing job postings, their salary ranges and their popularity throughout India ( Once the data set was processed, our group ordered the top roles for a particular “city” query and displayed linked information such as the number of job openings and average salary using a dictionary object for each job role. We then listed all the companies that were looking for this role and integrated the Google Custom Search Engine API to generate useful links based on keywords/skills needed for each job role. By feeding in websites such as Khan Academy, Medium, and Youtube, we were able to deliver a curated set of educational websites, articles, and videos to help individuals with interview preparation and eventual success for the specified profession.

Challenges we ran into

The first major task for our project was cleaning the data, which took a long time. Since there were 300,000 data entries. The data originally had many cells that we could not evaluate as they were very different from the other cells in the same columns. We continuously had to clean the data as we continued to work on the project. We often ran into errors when running our code since different “Locations”, “Roles, and etc. had very different inputs. The longest problem we had was setting a similar metric for “Salary”. There were about 20 different ways salaries were written throughout the 300,000 jobs, so we kept running into different errors when trying to show different salaries for different roles. We would say that the data cleaning was a very time consuming part, but definitely worth it by the end since it was essential in order to make our project look good.

Accomplishments that we're proud of

Some accomplishments we were proud of was learning how to utilize the Google Custom Search Engine API as well as learning Flask.

What we learned

As part of building Mauka, our group learned how to integrate our web application with the Google Custom Search Engine API and come up with a precise way of displaying relevant metrics for relevant job roles.

What's next for Mauka

Next steps involve devising a more powerful natural language processing algorithm for providing resources for one to explore when considering a listed position. We also plan to have a map where we could let users press on cities, and then a list of jobs in that city would show up. We might even add drop down menus for years of experience needed since we only used the jobs that were entry level.

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