Required Data Scraping,Microsoft Excel,Data Extraction,Machine Learning,API Integration freelancer for Data extraction from various formats & converted & formatted to Excell job

The Requirement - see more details & instructions in the attached word document.
To capture our Buyer's daily prices for agricultural commodities.
Our Buyer's prices for each commodity, & grade of Commodity change each day.
The below tasks are required to occur on a daily basis.
Our challenge is in capturing our Buyer's daily prices efficiently so we can compile, analyse & distribute them to our clients.
We receive our Buyer's daily prices in various formats - see points 1 to 6 below.
The formats or methods we receive our Buyer's daily prices are;
1. Pdf attached to an email. We must extract the data from the pdf, convert to Excel, & format to the Excel requirements buy correct cells, rows, columns & tabs so we can match up against the other buyers whose data must also be brought into the Excel spreadsheet.
2. Link within an email that opens a pdf file. We then must extract & format the data to Excel as per point 1 above.
3. Pictures inserted within an email. We then must extract & format the data to Excel as per point 1 above.
4. Text within an email. We then must extract & format the data to Excel as per point 1 above.
5. Visit the public website & navigate to the bid section & open a pdf. We then must extract & format the data to Excel as per point 1 above.
6. Over the phone, via SMS, & other digital apps. We then must manually enter this data into the Excel spreadsheet. I don't see a way around this, & we can manage this part ourselves, but require the ability to manually enter the prices.

We have multiple Buyers pricing on multiple commodities, & multiple grades of commodities at the same locations, on the same day, so it's important we can;
a. Collect all our Buyer's bids from their different source formats - see points 1 to 6 above.
b. Import them into the "Buyer Template" Excel file in the required format i.e. the format that exists in the "Buyer Template" for each Buyer (each Buyer Template is the same format),
c. Match them to the "Buyer Template" Excel columns headings of date, buyer name, site, crop year, commodity, grade, ntp, ntp price, gta location differential, site price, & delivery period.
d. Save each Buyer's prices in a separate Excel file.
e. Combine each Buyer's prices in an Excel file.

Skills & Expertise Required

Data Scraping Microsoft Excel Data Extraction Machine Learning API Integration