A training institute which conducts training for analytics/ data science wants to expand their business to manpower recruitment (data science only) as well.
Company gets large number of signups for their trainings. Now, company wants to connect these enrollees with their clients who are looking to hire employees working in the same domain. Before that, it is important to know which of these candidates are really looking for a new employment. They have student information related to demographics, education, experience and features related to training as well.
The client is a multi-national financial company, which offers multiple products to the consumers. There are multiple channels to offer these products to consumers although major contribution is coming from offline distribution channel. Offline channel sells Financial products to consumers via their agent network and as per government regulation these agents must be certified to sell financial products. There are multiple certification programs against different categories of financial products.
As this offline channel shares major contribution to total company sales, company focuses on recruitment and certify them to build large agent network. Here, major challenge is training them to get the certifications to sell various type of products.
Kiva.org is an online crowdfunding platform to extend financial services to poor and financially excluded people around the world.
Kiva lenders have provided over $1 billion dollars in loans to over 2 million people.
For the locations in which Kiva has active loans, your objective is to pair Kiva's data with additional data sources to estimate the welfare level of borrowers in specific regions, based on shared economic and demographic characteristics.
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