Creating a master file of all the historical pricing starting 2018 - present of teh PCBA components. Pre-processing the data:
- Loading that dataset into python and then removing the outliers and normalising the data to fit into the model.
- Fiting a Multiple Linear Regression Model and General Linear Model to determine the Target Price of the components based on historical pricing and its major cost-drivers.
This helped the Purchasing team at Tesla identify future cost saving opportunities, identify the best vendors and gain insights into the historical buying trends.