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APAC Strategy Intern - Customer Churn Modeling/Propensity To Buy Modeling

The Programme

Today, you might be stuck in the job you need, but at UPS, you can get the future you want. As a growing, dynamic Fortune 50 organization, we have the kind of opportunities that will help you go as far as your ambition will take you. You’re ready for bigger things, and we’ll get you moving in the right direction.

UPS APAC has a high demand for application of data science to various use cases. While we are ramping up our in-house system, we want to augment the capacity to generate additional value for the business during the year. The intern will be supporting the Demand Forecasting project to build machine learning models (classification and regression) and perform both customer churn and propensity to buy analysis.

What You Will Do

  • Historical customer profile and their decision on whether they bought our services or not is available.
  • Create datasets from various internal and external data sources to solve the problems.
  • Build models and codes to build customer churn models and propensity to buy models using classification techniques in machine learning.
  • Key success criteria would be measured in terms of out of sample prediction accuracy and in ranking the input variables in terms of variable importance factor.
  • Prescriptive Analytics needs to be performed for both models.

Required Skills and Abilities

  • Currently pursuing a Degree in Business/Data Analytics.
  • Equipped with sound knowledge on R/Python.
  • Ability to create usable data sets from documents and other sources of information.
  • Prior knowledge on building machine learning classification and regression techniques and variable importance analysis techniques.
  • Candidates should possess solid business sense.
Closed a year ago
Closed a year ago
  • Job type:Internships
  • Disciplines:

    Business and Commerce, Data Science and

    ...
  • Citizenships:

  • Locations:

    Singapore (Singapore)

  • Closing Date:21st May 2020, 6:00 pm

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