|
Description: |
I have two files- the driver file was @2.2mm records of consumers in the US- it contains information from estimates they received from a home improvement contractor- those data points include things like zip code, state, type of services, if sold or not, if financed or not, salespersons name, office, etc....
The second file is the results file that contains @1.6mm records- the results file is driver file where a credit file hit was matched. The results file has credit score, DTI, income, property value, cltv, equity position and a bunch of other credit data. this information is anonymized so no PII.
I am looking for someone to take this data and drive valuable insights by assessing both files individually, conversion rate, by sales person, average sale price, etc... on the driver file at a zip, agent and office level. Then perform a similar exercise on the results file to see what credit demographics exists at a zip level, also agent and office level. then merge the data at each levelt o create success metrics and insights from the combination of sales and credit information.
It can be as simple as a glorified pivot table up to a more in depth analysis to include some weighted scores and enriched data from other sources like census data.
I can work in an iterative manner and spend time with the consultant to refine results daily with new marching orders until it is complete. I may have other on-going work for the right person. I can provide detailed layouts, results and cuts that need to be performed. I would prefer someone with some knowledge of credit demographic data or they may not be able to contribute or the learning curve may be more dramatic. |
