Real Estate Data Miner Needed – Extract & Clean Property Ownership Data (Pompano Beach, FL)

Job ID: 40601023

Budget: $30 – $250 USD

I’m compiling a targeted list of single-family houses in Pompano Beach (NE, SE and SW sections only) that were purchased before Jan 1, 2022. Corporate entities and LLCs must be left out, but properties held in Trusts should remain. Also to be excluded are mailing addresses that are different to the property address, as this means it's being rented out.

For every qualifying address I need three data points: the current owner’s name, the street address of the property itself, and the owner’s separate mailing address. I’ll soon supply a list of local real-estate agents so you can filter out any of their holdings as well.

You may pull the information from public records, tax rolls, Broward County Property Appraisers office (BCPA.net) or any reliable data source you already use for property research and skip condominiums or multifamily parcels. Once gathered, organize the results in a clean spreadsheet; organized by streets. I prefer an Excel format.

I’ll review by spot-checking random entries against the county appraiser’s site, so accuracy matters more than sheer volume. Let me know your estimated turnaround and any clarifying questions you have before you start.
Please take a look at what I am requesting

Scope of Work
1. Extract Single-Family Homes
Pull all single-family residential properties located in:

NE Pompano Beach

SE Pompano Beach

SW Pompano Beach

Using ZIP codes:

NE: 33062, 33064

SE: 33060

SW: 33069

2. Filter Ownership Type
Include:

Individual owners

Trusts

Estates

Mailing addresses same as property address.

Exclude:

LLC

INC

CORP

LP / LLP

Holdings / Investments / Management entities

Properties whose mailing addresses are different to property address

3. Verify Ownership Date
Cross-check deed history to confirm the owner has held the property since before January 1, 2022.

4. Deliver Clean, Structured Dataset
Final dataset must include:

Property address - listed on the spreadsheet by streets. So for example, on the NE list, all the properties with the names of the owners and the full address, under NE 1st St, NE 2nd St, etc. However, I do need the full name of the owner and the full address under the NE 1st st column, etc.

Owner name

Mailing address must be the same as property address, exclude the ones that are not.

Ownership type (Individual / Trust / Estate)

Deed date (verified)

Neighborhood (NE / SE / SW)

Notes (e.g., absentee owner, trust type, long-term owner)

Format: Excel or Google Sheets

Required Skills
Strong experience with data mining, web scraping, or public records extraction

Ability to deliver accurate, verified data

Deliverables:

Complete dataset of qualifying properties

Clean, organized spreadsheet

SECONDLY

I need a list of properties where the mailing address is NOT in Florida. Same place, Pompano Beach, same zip codes and areas as before, NE, SE, SW. All found under www.BCPA.net.

To include:
Name
Address
Property address and mailing address.
Owned earlier than Jan 1,2021.
Single family homes
All kinds of ownership are ok.

To exclude from this list:
Mailing addresses in Florida.
Properties owned after Jan1 2022.

I need to know from you:
1. The total amount you will charge. So the amount you list on your proposal is what I'll assume you will charge. So please, no "holding fee" or "start to talk fee". Take a look at the job, ask me all the questions you need, then do a proposal.
2. Once I create a milestone, you need to accept right away. If you need time to think about it, I'll need to cancel it, because I don't want to waste time while you are thinking whether to accept or not.
Thus, ask me all the questions up front before you tell me a price , and once you say you can do it, please accept right away.
I look forward to working with you.
This will be an ongoing project, where I hope we can work well together.
Related categories: Excel Web Scraping Data Mining