# Assignment for Data Analyst

We are delighted to continue the recruitment process with you. Now it is your time to shine.
We’ve prepared a task for you so that you can prove your skills and to let us understand how
you are approaching problems in general. Good luck!

## Task
Attached to this message you’ll find a CSV file with some machine-generated user data of a
service like Wolt. Every row of the dataset represents one customer who has registered to use
the service during September 2019 and either has or hasn’t made orders during the time from
then and October 2020.

Your assignment is to

1) Familiarise yourself with the dataset. Here you should show us your excellent exploratory
data analysis skills.

2) Provide us with a user segmentation that could be utilised by our marketing team to
reactivate different kinds of users. Provide also recommendations on how to use the
segmentation for this purpose. Remember to justify your segmentation approach so that we
understand why the way you did it is better than an arbitrary solution by a non-data analyst
who can do some slicing-and-dicing with the data.

## Our expectations
At Wolt we use Python or R for notebooks and we expect you to return the rendered notebook
alongside the code used for the analysis. Make sure we can run and view your solution on
MacOS and Linux.

In addition to the notebook used to solve the assignment, please include a separate supporting
presentation that highlights the main steps of the analysis and communicates your findings. As
a further guideline, the presentation should be self-sufficient for us to follow your thoughtprocess when solving the assignment: Please explain why you decided to go with this
particular approach and what could be the pros and cons of applying it.

Please note that time spent on the assignment may vary but it normally takes around 8 hours
to complete. We hope you will return the assignment within 7 calendar days of receiving it.

Best of luck! We can’t wait to see how you approach challenges like these.
👋