/Walmart-Store-Sales-Forecasting

We are provided with historical sales data for 45 Walmart stores located in different regions. Each store contains a number of departments, and you are tasked with predicting the department-wide sales for each store. In addition, Walmart runs several promotional markdown events throughout the year.

Primary LanguageJupyter Notebook

Walmart-Store-Sales-Forecasting

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In this recruiting competition, job-seekers are provided with historical sales data for 45 Walmart stores located in different regions. Each store contains many departments, and participants must project the sales for each department in each store. To add to the challenge, selected holiday markdown events are included in the dataset. These markdowns are known to affect sales, but it is challenging to predict which departments are affected and the extent of the impact.

Want to work in a great environment with some of the world's largest data sets? This is a chance to display your modeling mettle to the Walmart hiring teams.

This competition counts towards rankings & achievements. If you wish to be considered for an interview at Walmart, check the box "Allow host to contact me" when you make your first entry.

You must compete as an individual in recruiting competitions. You may only use the provided data to make your predictions.

Business Context:

The objective is predicting store sales using historical markdown data. One challenge of modelling retail data is the need to make decisions based on limited history. If Christmas comes but once a year, so does the chance to see how strategic decisions impacted the bottom line.

Data Availability & Business Problem:

You are provided with historical sales data for 45 Walmart stores located in different regions. Each store contains a number of departments, and you are tasked with predicting the department-wide sales for each store. In addition, Walmart runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of which are the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the challenge presented by this competition is modelling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data.