About

We have a master Excel file (FL_Loan_Originators_Master_List.xlsx) with ~21,800 Florida loan officers. Your job is to fill in the Sponsoring Company column by pulling data from the NMLS Consumer Access website (https://www.nmlsconsumeraccess.org ). This project cannot be done manually — automation is required. Target completion: 7 days (you must be able to process 3k–5k IDs per day). What Went Wrong (Previous Attempts) A previous VA tried this with Octoparse and was blocked by CAPTCHA on every search. Without rotating residential proxies and captcha-solving integration, the workflow collapsed. The VA fell back to manual lookups, which is impossible at this scale (21,800+ records). Key lesson: Point-and-click scrapers without advanced setup will fail. What You Need (Requirements to Succeed) You must already have: ✅ Rotating residential proxies (datacenter IPs are not sufficient) ✅ Captcha-solving integration (2Captcha, AntiCaptcha, CapMonster, etc.) ✅ Headless browser automation (Playwright, Puppeteer, Selenium, or Apify actor) ✅ Error handling & retry logic built into your workflow ✅ Ability to process 20k+ IDs in batches without breaking ❌ Not acceptable: Manual lookup Simple point-and-click scrapers (Octoparse, ParseHub, etc.) without captcha/proxy support Deliveries with blanks, mismatched IDs, or partial work ⚠️ Risk Factors If you are inexperienced, you will lose 2–3 days debugging captcha/proxy issues. If your proxies are weak or banned, throughput will slow way down. If you don’t already have automation infrastructure, there is no chance of finishing in 7 days. Deliverables Completed Excel file: FL_Loan_Originators_Master_List_Completed_[YYYY-MM].xlsx Sponsoring Company column filled with either: Exact company name, OR None if profile shows “Represents: None” Milestones (Total Budget: $200 Fixed) Milestone 1 — Proof of Automation (Test Batch) Scope: Scrape 1,000 provided NMLS IDs → return CSV with NMLS_ID + Sponsoring_Company Budget: $20 Due: 24 hours Pass/Fail: All 1,000 results accurate, no blanks, “None” where applicable Milestone 2 — Partial Batch (Validation Run) Scope: Scrape 10,000 NMLS IDs (random sample) Budget: $50 Due: 2–3 days Pass/Fail: Random QC checks vs NMLS site must match exactly Milestone 3 — Full Scrape Scope: Scrape all remaining ~10,800 IDs and deliver as CSV Budget: $100 Due: 5–7 days Pass/Fail: Sponsoring Company column 100% filled (company name or None) Milestone 4 — Final Merge & Delivery Scope: Merge results into master Excel (FL_Loan_Originators_Master_List.xlsx) using NMLS_ID as the key. Deliver updated file back via Dropbox. Budget: $30 Due: 1 day Pass/Fail: Column alignment verified, no mismatched companies, file named correctly How to Apply In your application, please answer: Which captcha-solving service have you integrated before? Which proxy provider do you use for residential IP rotation? Which automation framework (Playwright, Puppeteer, Selenium, etc.) will you use? Share a brief example of a large-scale scraping job you’ve successfully completed. Only applicants who can demonstrate experience with proxies + captcha solvers + headless automation will be considered.