Marketing Data Science with Python

Overall Goal: Create a model to identify the customers more likely to accept offers.


1) Identify and justify statistically what is the best approach for our problem (classification -i.e. will accept or not-, regression – i.e. the ones that will leave more $-, or expected value -i.e. a x b). At the end our objective is the revenue (we prefer one customer using our product for $1000 than 10 customers using it for $80 for example)

2) Identify and justify the selection of the best model as well as the selection of the best features to be used (our dataset contains +300 features, we expect to end up with 5 to 8)

The work must be presented in a python notebook, with comments and proper justification (ideally statistically)


We have 3 previous campaigns results where we used a custom model. Using the output of this model will possibly bias the new model, for that we have executed a control group in our full customers ‘universe for which we also have the results. The data scientist should define a strategy indicating best way to maximize all the results we have.

Skills: Machine Learning (ML), Python, Statistics

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About the Employer:
( 0 reviews ) Dallas, United States

Project ID: #23419841

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