We are a top electronic component and fastener distribution company looking for a machine learning expert to assist us in developing a pricing model for our e-commerce.
3.7 million products need tiered pricing generated based on a cost + margin model.
So far, we imagine that the input values will be part number, quantity sold, brand (PRC) and unit cost. These values are generated based on sales history priced by our sales force. There are about 130K rows of data for a 6 month period (we can pull more data as needed). The predictive output will be profit margin.
Product Example:
Part Number 56-10-11
Quantity: 1-10
Price: $1.00
Quantity:11-50
Price: $.90
Project Deliverables:
3.7 million products to be priced with 24 quantity tiers (with predicted profit margin).
Model that can be used to generate pricing for our e-commerce site and update the model based on new quantity, cost and brand data.
Since our objective is to generate pricing reflective of market average we are utilizing our RMSE of the model as a key performance indicator. Ideally, we would like to predict within 5% of the actual margin.
Project Files:
I have included screenshots of: sample data we have, what predicted output may look like and what the machine learning code may look like in Python.
If this sounds like something that might be a good fit please let me know and we can discuss.
About the recuiterMember since May 20, 2018 Chatinder Banga
from Berkshire, United Kingdom