Email data extraction (unstructured text)

We are a leading Canadian provider of freight transportation services with approximately 1,000 employees worldwide.

We are currently seeking a freelancer to build an app capable of extracting and organizing into a database (or Excel spreadsheet) specific quote-related information from emails. The emails containing the information are unstructured and highly variable. The information we need to extract and organize from each email includes, but is not limited to:

- Origin City

- Origin State

- Origin Country

- Destination City

- Destination State

- Destination Country

- Mode (Dry van, reefer, flat bed, Less-than-truckload, rail, etc...)

- Customer/Company name (from email)

- Sending rep (from email)

- Date/Time

- Quoted rate

- Quoted currency

- Quote format (Rate-per-Mile-all-in; Rate-per-mile-linehaul-only; flatrate-all-in; flatrate-linehaul-only)

- Quote duration

- shipment frequency

- shipment weight

- Miscellaneous freight characteristics: is it hazardous, does it require tarping, does it require permits, does it require team-drivers... (a more comprehensive list of freight characteristics will be provided to the awarded freelancer)

The finished app needs to be capable of efficiently processing a high volume of emails in a variety of formats (.pst, .ost, .nst, .docx, .doc). As well it is extremely important that the accuracy/confidence level be high (95%+).

Further details available upon request. Preferential consideration given to applicants with experience in the transportation industry.

Skills: Machine Learning (ML), Python, Software Development, Data Mining, Data Analytics

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About the Employer:
( 0 reviews ) Toronto, Canada

Project ID: #27510440

19 freelancers are bidding on average $2252 for this job

(7 Reviews)
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(8 Reviews)

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(13 Reviews)

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(18 Reviews)

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(1 Review)

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(3 Reviews)

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(5 Reviews)

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(2 Reviews)

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(1 Review)

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(0 Reviews)

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