Efficient Data Extraction for Freelancers

Role overview

We're a growing business with increasing automation and AI implementation needs, and we're looking for a skilled **part-time n8n Automation Developer** to take ownership of designing, building, and maintaining our automation ecosystem.

This is an ongoing engagement starting at approximately **10–15 hours per week**, with a flexible schedule and the potential for long-term collaboration as our automation requirements continue to grow.

What We're Looking For

We're looking for someone who is highly experienced with **n8n** and can independently build, deploy, and maintain production-ready automation workflows from start to finish.

You'll be responsible for creating reliable, scalable automations that streamline business operations, eliminate repetitive manual tasks, and integrate multiple business applications into a seamless workflow.

Your responsibilities may include:

* Building complex n8n workflows from scratch
* AI-powered workflow automation using OpenAI, Claude, Gemini, or similar LLMs
* AI agents for customer support and internal operations
* Lead capture, qualification, and routing
* CRM integrations and synchronization (HubSpot, Salesforce, GoHighLevel, Pipedrive, etc.)
* Email, SMS, and WhatsApp automation sequences
* API integrations with third-party SaaS platforms
* REST API development and webhook implementations
* OAuth and API authentication handling
* Database integrations (PostgreSQL, MySQL, MongoDB, Airtable, Supabase, etc.)
* Document processing and OCR automation
* Data extraction, transformation, and synchronization
* Google Workspace automation (Sheets, Drive, Gmail, Calendar)
* Slack, Discord, Microsoft Teams, and internal notification systems
* Invoice, payment, and accounting platform integrations
* Custom business process automation
* Error handling, logging, monitoring, and workflow optimization
* Debugging, maintaining, and improving existing automations

You should be comfortable reading API documentation, working with webhooks, troubleshooting integration issues, handling authentication methods, and deploying workflows with minimal supervision.

Preferred Experience

We're particularly interested in candidates who have hands-on experience with technologies such as:

* n8n
* OpenAI, Claude, Gemini, or other AI APIs
* Make.com, Zapier, or similar automation platforms
* REST APIs and webhooks
* JavaScript or Python for custom automation logic
* CRM platforms
* Google Workspace APIs
* Communication platforms (Twilio, WhatsApp, SMS, Email)
* Cloud databases and SaaS integrations

Experience building AI-powered automation systems that solve real business problems is a significant advantage.

To Apply

Please share *real production work*, not tutorial projects or demo workflows.

For at least *2–3 automation projects*, include:

* What business problem you solved
* Which platforms and tools you integrated
* Your specific role in the project
* The complexity of the workflow
* Any AI components or custom logic you implemented
* The measurable business results or efficiency improvements achieved

We're looking for someone who can think through business processes, recommend improvements, and build reliable automation solutions that can scale with our business.

We are looking for an experienced Python Web Scraping Expert to help us build and maintain reliable, scalable data extraction solutions, with a focus on Chinese websites.
This role requires strong technical expertise, attention to detail, and the ability to solve challenges independently.

🔧 Responsibilities
- Develop and maintain web scraping solutions using Python
- Analyze website structures and build efficient, scalable data collectors
- Improve and optimize existing data extraction processes
- Troubleshoot issues across data pipelines and ensure data quality
- Collaborate with internal teams and external partners
- Take ownership of tasks and deliver reliable solutions

🧠 Required Skills
- Strong Python experience (e.g. Scrapy, Requests, Selenium/Puppeteer)
- Proven experience in web scraping / data extraction / crawling
- Good understanding of HTTP, APIs, and web technologies (HTML/CSS)
- Experience with XPath or Regular Expressions
- Familiarity with Git and Linux environment
- Experience using browser developer tools and Postman

Every new-lead notification lands first in my Outlook inbox and I no longer want to copy-paste the details into GoHighLevel. What I need is a reliable automation that will:

• watch the inbox for incoming Outlook Emails that contain lead data from each of my three generators. All 3 emails templates are different.
• extract the prospect’s name, email, phone, address, lead source.
• create a new lead record inside GoHighLevel the moment the email arrives
- Set the lead pipeline to Sales pipleline and stage to New Leads.
- I also need the address field in GHL edited so that it automatically searches for addresses when manually entering into contacts files.

These need to be done within GoHighLevel i do not want to use a 3rd party to automate.

Acceptance criteria
1. A test email from each generator automatically appears as a correctly populated lead in my GHL account.
2. The lead is filed under the appropriate source tag.
3. No duplicates are created on repeated sends.

If you’ve connected Outlook and GoHighLevel before, let’s make this live.

This needs to be done today.

Skills: Data Processing, Data Entry, Excel, Web Scraping, Email Handling, Data Extraction, Lead Generation, Automation, API Integration, GoHighLevel

We are seeking a skilled freelancer to assist with a meta-analysis protocol examining the effects of nitrogen and phosphorus enrichment on grassland biodiversity and ecosystem. The project involves conducting a systematic literature review, data extraction, and statistical analysis to synthesize findings. The ideal candidate will have experience in meta-analysis and data interpretation, particularly in environmental science contexts. The project aims to provide insights into the impacts of nutrient enrichment on grassland ecosystems.

We are looking for an experienced researcher with a strong background in systematic reviews and meta-analyses in the medical or healthcare field.

The ideal candidate should have hands-on experience conducting high-quality systematic reviews in accordance with PRISMA guidelines and be proficient in all stages of the review process.

Responsibilities
Assist with systematic review and meta-analysis projects from protocol to manuscript.
Develop and refine search strategies.
Perform literature screening (title/abstract and full-text).
Extract data accurately from eligible studies.
Conduct risk of bias/quality assessment using appropriate tools (e.g., Cochrane RoB, Newcastle-Ottawa Scale, ROBINS-I, QUADAS-2, etc.).
Perform statistical meta-analysis using software such as RevMan, R (meta/metafor), Stata, or Comprehensive Meta-Analysis (CMA).
Generate forest plots, funnel plots, sensitivity analyses, subgroup analyses, and publication bias assessments as needed.
Assist with manuscript writing, interpretation of results, and preparation of publication-ready tables and figures.
Revise manuscripts based on journal or reviewer comments when required.
Preferred Qualifications
Master's, PhD, MD, or equivalent experience in Medicine, Public Health, Epidemiology, Biostatistics, or a related field.
Proven experience completing and publishing systematic reviews and meta-analyses.
Strong understanding of PRISMA, PROSPERO registration, and evidence synthesis methodology.
Excellent scientific writing and communication skills.

To Apply

Please include:

A brief summary of your experience with systematic reviews and meta-analyses.
Links, DOIs, or PDFs of 2–5 published systematic reviews/meta-analyses you have worked on.
The software you use for meta-analysis.
Your role in previous projects (screening, data extraction, statistical analysis, manuscript writing, etc.).
Your availability and estimated turnaround time.

Saya ingin mendapatkan gambaran jelas dan mudah dipahami mengenai data yang tersimpan di database MYOB kami. Fokusnya analisis deskriptif—statistik dasar, tren utama, outlier, serta visualisasi ringkas yang membantu tim non-teknis memahami pola data.

Ruang lingkup:
• Ekstraksi data langsung dari database MYOB (format ODBC atau dump yang saya sediakan).
• Pembersihan ringan bila diperlukan agar hasil statistik konsisten.
• Pembuatan ringkasan numerik (mean, median, sebaran, frekuensi, dsb.).
• Visualisasi sederhana—bar, line, atau pie chart—menggunakan Python (pandas, matplotlib/seaborn) atau alat BI lain yang Anda kuasai.
• Penulisan “data story” singkat (1-2 halaman) yang menjelaskan temuan utama dengan bahasa awam, lengkap dengan insight yang dapat segera ditindaklanjuti.

Akses database, contoh query awal, dan struktur tabel akan saya berikan setelah kick-off. Saya menghargai komunikasi terbuka; sampaikan metode apa pun yang Anda anggap paling efisien. Hasil akhir saya harapkan dalam bentuk file laporan (PDF/Docx) beserta skrip atau notebook analisis sehingga bisa direplikasi di masa mendatang.

Skills: Python, Data Processing, Excel, SAS, Statistical Analysis, Data Extraction, Data Visualization, Data Analysis

I have paid more than 108k+ USD to freelancers in last few months. I have worked with more than 130 developers here and currently working with 130 developers.

I am looking to get my automation script fixed

I prefer a developer based in the UK, or someone who can reliably test against the UK version of the website.

I need every photo from my personal Instagram and Facebook accounts copied in full resolution and placed onto a USB stick I’ll supply. Please mirror my existing album structure on the drive so each Facebook album—and the equivalent groupings from Instagram—has its own folder. Inside those folders, rename the image files by the date of the original post (YYYY-MM-DD) so they appear in proper chronological order when viewed.

The job is complete when I can plug the USB into either a Mac or Windows computer, open the folders, and see every picture correctly dated and in the right album without any missing or corrupted files. A short text log listing the total number of images retrieved (and noting any that could not be downloaded) will help me confirm everything is there.

If you’re comfortable handling bulk downloads from social platforms and careful about file organisation, I’d love to hear how quickly you can turn this around.

Skills: Data Processing, Data Entry, Excel, Virtual Assistant, Social Media Management, Data Extraction, Data Management, Data Backup

We need an AI/automation expert to build a system that automates our accounts payable processing and bank reconciliation across Outlook, Xero, and OneDrive — including document handling, data extraction, and GL coding logic.

Please include available start date and expected number of hours to compete.

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Summary (SEE ATTACHED FILE FOR DETAILS)
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We are looking for a detail-oriented Data/Web Scraping Specialist to extract public records data.

The goal is to generate 1 comprehensive dataset of cases and their features by iterating through specific case number sequences.

The final deliverables are 1 dataset including 14 columns (County; Case Number; Case Name; Filing Date; Type; Status; Court; First Name; Middle Name; Last Name; Suffix; Party (Plaintiff/Defendant); Events / Hearings; and Events / Hearings (cont.)).

The deliverable should contain as many rows as necessary according to the number of attorneys in the cases. The scripts necessary to do this process should be included as a part of the deliverable for auditing purposes.

Please ensure that the data is presented in a clear and organized format.

Due date: 07/31/2026 11:00 CST

I have a large list of Florida HVAC companies that I need enriched using the same system and pricing as you have with Robert:

* $0.20 for the owner’s name and verified direct email
* $0.10 for the owner’s name with a generic company email

For each company, please find:

* Owner’s first name
* Owner’s last name
* Direct owner email
* Generic company email if no direct email can be found
* Source link showing where the owner’s details were found

Please use this colour code:

* Green — verified direct owner email
* Yellow — verified owner name but generic company email
* Red — owner or usable email could not be found

If there are multiple owners, please add every owner on a separate row and duplicate the company details. We want to email every possible owner or key decision-maker.

We only want the owners or key decision makers for the company. If no owner can be found and someone is clearly the highest decision-maker with nobody above them, include them.

Please do not rely only on LinkedIn. Many companies have the same name, which can result in the wrong person being matched. Cross-reference the company and location using other public sources. We have had a bad experience with people using LinkedIn only for enrichment, it’s very unreliable in this industry.

We have included the full company address, so whenever you are unsure, please use it to confirm that you have found the correct company and person.

If you find the owner but cannot immediately find their email, please manually test likely email formats, for example formats like:

* firstname @company.com
* firstname. lastname @company.com


Let me know once you are ready for the sheet.

Thank you!

We seek a self-motivated freelancer who can scrape the Canadian ISBN directory for us. We pay $20 for the whole directory plus up to $100 for each author we contact who signs-up for our book production or marketing services.

We focus on books with a human rights and social justice orientation.

Need to collect certain type of figures of both x,y from different publications during the period 2000-2025 and expected to get more than 80 figures. Once it is found then arrange the prompt to place it all in one figure. Then ask Ai to unify the figures to be in one final figure bearing in mind that figures should be well organize and legend is clear showing each element with the clearly noted text.
As the facilities available in Ai, digitizing the figures became now so easy and can be done automated so exploit this oppertunity for a better presentation of the final figure

We are seeking a skilled freelancer to extract a Bill of Quantities (BOQ) from a CAD file. The ideal candidate will have experience in CAD software and quantity surveying, ensuring accurate data extraction. Attention to detail is crucial for this task. The project is part-time and expected to be completed in less than a month.

I have fewer than 50 editable-text PDF surveys that need to be transcribed into the spreadsheet template I’ll supply. Every response, including fields that contain special characters, must land in the correct column with the exact formatting the template expects—no stray spaces, mismatched date formats, or typos.

Here’s the workflow I’m envisioning:
• You open each editable PDF, copy or extract the answers, and paste them into the matching columns of my template.
• You keep an eye on diacritics and other special symbols so they render exactly as in the original.
• After entry, you run quick source-to-sheet spot-checks (totals, counts, or sample records) to confirm everything aligns with the PDFs.

Deliverable:
• One fully populated spreadsheet ready for analysis, error-free and consistently formatted.

If you’ve handled PDF-to-sheet data extraction before and pride yourself on clean, reliable data entry, let’s get started.

Skills: Data Processing, Data Entry, Excel, PDF, Data Cleansing, Data Extraction, Data Management, Data Annotation

Summary
comparison of bids given by different companies
1. moving them onto the same file
2. comparing manually and normalizing them (finding the differences and bringing them to the same basis

comparison of bids given by different contractors
1. moving them onto the same file
2. comparing manually and normalizing them (finding the differences and bringing them to the same basis

# Python/AWS Developer Needed: Complete Probate Lead-Gen Pipeline (Gemini AI + SQLite + Google Sheets) — 2 Day Turnaround

## About the project

I run a single-family real estate investment company in Metro Detroit. I already have a working, in-production lead-generation pipeline that:
- Runs 24/7 on an AWS EC2 instance as a systemd service
- Monitors PDF issues for mortgage foreclosure notices
- Uses Google Gemini AI to extract structured data from the PDFs
- Matches extracted leads against a 1.3M-row property database (SQLite, built from ATTOM bulk data: tax assessor, AVM, and recorder files)
- Writes enriched leads to Google Sheets

I'm extending this same system to also capture **probate leads** — decedent estate and trust notices from the same PDFs — matched against the same property database by **owner name** instead of address (since probate notices give you a name, not an address).

A lot of the groundwork is already built. I need someone experienced to test it against real data, fix what breaks, close the remaining gaps, and ship it.

## Current state (being fully transparent about this)

The following code has been written but **not yet tested against the live Gemini API or the production database** (developed in an environment without API/network access):

1. `gemini_notice_extractor.py` — sends the PDF to Gemini, extracts probate creditor notices, trust notices, and appointment hearings as structured JSON via a Pydantic schema. Passes a syntax check; has not been run against real Gemini output.
2. `unified_enrichment_builder.py` / `unified_enrichment_service.py` — patched versions of my existing enrichment-database code, adding owner-name search (new columns: owner name, trust/company flag, owner mailing address). Tested locally against synthetic data matching the real schema; not yet run against my actual 1.3M-row production file.
3. `dln_probate_processor.py` — ties extraction and property-matching together into one pipeline.

All code, my existing repo's relevant files (`unified_enrichment_service.py`, `unified_enrichment_builder.py`, `pdf_monitor.py`, `DEPLOYMENT.md`), and a written spec of the matching/confidence-scoring logic will be provided to whoever takes this on.

## What I need you to do

1. **Test and debug the Gemini extraction** against real PDF issues. Fix any schema mismatches or extraction accuracy issues (missing fields, misclassified notice types, etc.).
2. **Rebuild my enrichment database** with the new owner-name columns (script is already written, ~15-20 min one-time job) and verify match quality against real decedent names.
3. **Wire up Google Sheets output** — a 4-tab structure (raw notices / unique cases / property matches / qualified leads), using my existing service-account credentials.
4. **Decide and implement the integration point**: either a standalone script/cron job, or — likely better — folded directly into my existing `pdf_monitor.py` polling loop, since it may already be fetching this same PDF for foreclosure notices. Your call once you've seen the code.
5. **Handle deduplication**: notices are sometimes printed twice in the same issue (same case number) and must collapse to one case, not one row per printing.
6. **Deploy as a systemd service** on my existing EC2 instance, matching the pattern my current `pdf-monitor.service` already uses.
7. **Basic QA** across a handful of real PDF issues — confirm accuracy on decedent name, PR/trustee contact info, and property match quality before calling it done.

## Tech stack

Python 3, Google Gemini API (`google-genai` SDK), Pydantic, SQLite, Google Sheets API (`gspread` + service account auth), AWS EC2 (Ubuntu, systemd), Google Drive API.

## Required experience

- Strong Python — comfortable reading and extending an existing codebase quickly, not just writing from scratch
- Experience with LLM structured-output extraction (Gemini, OpenAI function calling, or similar) — you should know what schema mismatches typically look like and how to fix them fast
- SQLite / data pipeline experience at the "a few million rows" scale
- Google Sheets API / service account authentication
- AWS EC2 + Linux systemd (comfortable SSHing in, managing a service, reading logs)
- Familiarity with real estate data, ATTOM property data, or probate/foreclosure lead generation specifically

## Deliverables

- Working end-to-end pipeline, tested against at least 3-5 real DLN PDF issues
- Enrichment database rebuilt and verified with owner-name search working
- Google Sheets output live and populating correctly
- Deployed and running unattended as a systemd service
- Short written summary of what you changed/fixed and any known limitations
- Available for a brief handoff call

## Timeline & budget

**Need this completed within 2 days of start.** Given the amount of existing groundwork, this should be realistic for someone with the right background — but please review the attached code before committing to the timeline, since the honest state is "built but untested," not "fully working." I'd rather have an accurate estimate than a missed deadline.

Please quote a fixed price for the full scope above, and let me know your availability to start immediately.

## To apply

Please include:
- Relevant experience with LLM-based data extraction and/or property data pipelines
- Your proposed fixed price and confirmation you can start right away

I have a set of completed survey forms saved as PDF files. I need every response transferred accurately into a structured spreadsheet so I can run my analysis without worrying about transcription errors.

Here’s what I’ll provide:
• All PDF survey files, clearly named
• A blank template spreadsheet with the exact columns and field formats I need

What I expect back:
• One completed spreadsheet populated with every survey response
• Consistent formatting (no typos, extra spaces, or mixed date styles)
• Source-to-sheet spot-checks so totals line up with the originals

If you have experience extracting data from PDFs and a track record of clean, reliable data entry, I’d love to work with you.

Skills: PDF, History, Data Extraction, User Story Writing

We are looking for an experienced Lead Generation & Email List Building Specialist to build high-quality, verified B2B/B2C prospect lists for targeted outreach campaigns.

Responsibilities:

- Research and identify targeted prospects based on specific criteria.
- Build accurate email lists with names, job titles, company details, and verified email addresses.
- Collect additional data such as LinkedIn profiles, phone numbers, websites, and locations when required.
- Ensure all leads are up-to-date, accurate, and have low email bounce rates.
- Deliver organized data in Excel or Google Sheets within the agreed deadline.

Requirements:

- Proven experience in lead generation and web research.
- Expertise with tools like Apollo, LinkedIn Sales Navigator, ZoomInfo, Hunter, Snov.io, Lusha, and similar platforms.
- Strong attention to detail and commitment to data accuracy.
- Excellent communication skills and ability to meet deadlines.

Hi we're looking for a reliable and consistent data entry specialist to spend 5-10 minutes a day entering in data from meta ads, go-high-level, ChatGPT, and sales data into google sheets. This is for a long-term contract, and we'd like to find someone who can learn quickly, and jump on occasional calls (PST) to talk through data entry needs.

If you'd like to apply, let me know and we can assign a paid trial for a data assignment for 30 minutes.

Thank you.

Job Title
Hiring Dedicated 5-Person Tech Team (PM, Python Scraper, Django Architect, Flutter/React Dev, UI/UX)

Job Description
We are seeking a dedicated, high-performing 5-person project team (or individual specialists forming a team) to design, build, and deploy an end-to-end B2B Lead Acquisition, Sales Automation, and Internal Workforce Platform.
The software consists of 6 integrated modules covering data extraction, multi-channel client outreach, real-time team messaging, and workforce productivity.

Key Modules & System Scope
Module 1: Data Scraper Pipeline — High-performance B2B directory & active job posting scrapers with anti-bot bypass and proxy management.
Module 2: Client Pipeline & Sales CRM — Kanban-style task tracking, daily sales goals, and client status dashboards.
Module 3: Multi-Channel Client Outreach — Cold email automation, web-to-SMS, VoIP/SIM call logging, and multi-channel messaging integrations.
Module 4: Calendar & Meeting Engine — Two-way sync (Google/Outlook), booking links, and automated meeting reminders.
Module 5: Proprietary Team Chat App — Standalone cross-platform (Mobile & Desktop) real-time messaging system using WebSockets.
Module 6: Workforce Management — Desktop monitoring agent for screenshot capture, time logging, and app/website activity tracking.

Required Team Roles & Tech Stack
We are hiring for the following 5 distinct roles:
1x Technical Product Manager / Project Lead: Agile sprint management, technical QA testing, code review, and milestone delivery.
1x Senior Data Extraction Engineer: Python, Scrapy, Playwright/Selenium, Proxy Rotation, Cloudflare Bypass.
1x Lead Backend Architect: Python, Django REST Framework, PostgreSQL, Django Channels (WebSockets), Redis, Celery.
1x Cross-Platform Mobile & Frontend Engineer: React.js (Web Dashboard), Flutter (iOS/Android/Desktop Chat), Electron.js (Desktop Agent).
1x UI/UX Designer: Figma wireframes, component design systems, and responsive layouts.

Project Standards & Architectural Requirements
Modular Monolith Architecture Requirement: The backend must be built using a Modular Monolith architecture in Django. Each of the 6 modules must exist as an independent, loosely coupled app directory with its own API endpoints and database models. The system must support Role-Based Access Control (RBAC) and Feature Flags so that any individual module can be enabled, disabled, or accessed as a standalone tool per organization account.
Unified Core Backend: Core backend MUST be built strictly using Django REST Framework + PostgreSQL.
Code Ownership & Security: Daily Git commits forced directly to our company GitHub repository. Developers work with seed/dummy datasets; no raw production keys are exposed.
Deployment Readiness: All completed modules must include Docker containers and fully documented setup guides (README.md).
Execution Model: 2-week Agile Sprints with mandatory visual demos at the end of each sprint.

How to Apply
Please submit your proposal with:
Portfolio links or case studies of similar complex platforms (Scrapers, CRMs, or Messaging Apps built in Django/React/Flutter).
A breakdown of whether you are applying as an established team or an individual specialist for one of the 5 roles.
Your estimated timeline and milestone/hourly rate expectations

Skills: Python, Web Scraping, Django, Software Architecture, PostgreSQL, Redis, React.js, Scrapy, Flutter, Selenium

We are a real estate firm and need a detail-oriented person, comfortable extracting data from real estate documents, to review broker Offering Memorandums, financials, and rent rolls (PDF and Excel), pulling key data points and flagging any inconsistencies.

i need you to make me a python script to extract login info like a info stealer and send to a discord webhook, DO NOT RESPOND TO ME WITH AI and dont waste my time by messaging saying "unethical" I WILL PAY BIG MONEY!

Skills: PHP, Python, Linux, Data Processing, Software Architecture, Scripting, Data Extraction, API, Automation, Discord

I need a freelancer to extract historical pricing data for a defined set of target products across four e-commerce websites, using the Internet Archive's Wayback Machine (and other web archives where needed) — going back as far as records exist.

This is a backward-looking / archival data project, not a live monitoring project. I want to reconstruct a price history timeline: what these sites charged for specific products, and how those prices changed, from whenever archive records begin up to today.

SCOPE

- 4 target websites, all within the same retail category. One of the four is no longer operating and is only reachable via web archives. Full URLs will be shared directly with the freelancer I engage (not published publicly for confidentiality reasons).
- A defined list of target products (specific branded product lines/SKUs within a single retail category). The full product list will be shared with the freelancer I engage.

WHAT I NEED DELIVERED

1. A coverage report — for each site, how far back does archive data actually go, and how complete/sparse is it? I want honesty here, not just a data dump — if a site has poor coverage, tell me.
2. A structured spreadsheet (CSV or XLSX) with columns: date, competitor, product_name, SKU/variant, price, source (URL + archive snapshot link), notes.
3. Missing data marked clearly — use "n/f" (not found) rather than estimating or interpolating. Every number in this file needs to be a real, sourced price.
4. Methodology notes — which archive sources you used (Wayback Machine, archive.today, Common Crawl, etc.) and why, per site.
5. Optional add-on, quote separately — a simple forward-looking scraper that continues logging these same prices going forward, so historical and future data connect into one continuous timeline.

TECHNICAL STARTING POINT

I already have a basic Python starter kit (Wayback Machine CDX API probe + scraper scaffold) I can share once engaged — you're welcome to use it as a base, rebuild it, or use your own approach/tools. What matters is the result: accurate, sourced, dated pricing data going as far back as possible.

REQUIRED SKILLS

- Python (requests/urllib + BeautifulSoup or lxml)
- Direct hands-on experience with the Wayback Machine CDX API specifically (not just general scraping)
- Regex / structured data extraction from HTML
- Data cleaning with pandas or similar

PREFERRED, NOT REQUIRED

- Experience with archive.today or Common Crawl as a fallback source
- E-commerce site experience (product schema, JSON-LD pricing markup)
- Prior work on price-history reconstruction or competitor price monitoring projects

IDEAL FREELANCER

- Comfortable telling me what's not possible, not just what is — I'd rather know a site has thin archive coverage than get a spreadsheet padded with guesses
- Can document their sourcing clearly enough that I can verify any given number myself

BUDGET & TIMELINE

Please quote as a fixed price for the full 4-site historical backfill, based on the scope above. If you believe an hourly arrangement makes more sense given uncertainty in archive coverage, propose a not-to-exceed estimate with milestones (e.g., "coverage report" as milestone 1, before committing to full extraction).

Target timeline: 1–3 weeks depending on archive depth and site complexity.

SCREENING QUESTIONS

1. Have you worked with the Wayback Machine CDX API or similar historical archive tools before? Briefly describe a past project.
2. Based on general experience, what's your rough sense of how deep Wayback Machine coverage typically goes for small-to-mid-size e-commerce sites?
3. What's your approach when a site has poor/no archive coverage — do you have fallback methods?
4. Please quote a fixed price and rough timeline for this scope.

I need data scraped from the Google and relevant sources. The final result should be a clean, well-structured CSV (or Excel) file that lists each business’s name, the phone number, address, and the exact URL where the number appears so I can verify the data quickly.

Work Description:
Need data of all the doctors in India. Need data of all the hospitals, clinics, and medical facilities in India.

Key points I care about:
• Accuracy: only valid, fully-formatted phone numbers.
• Efficiency: the scrape should run unattended and respect reasonable rate limits so IPs don’t get blocked.
• Reusability: deliver the source code (Python, Scrapy/BeautifulSoup/Selenium—use what you prefer) plus a brief README so I can rerun the extraction later or point it at new URLs.

Let me know how you plan to tackle CAPTCHAs or dynamically loaded pages, and provide an estimated turnaround time along with a short sample to show the approach works.

Skills: JavaScript, Python, Data Processing, Excel, Web Scraping, Data Mining, Scrapy, Data Extraction, BeautifulSoup, Data Management

Hi, I’m looking for someone to help me compile a list on non preforming mortgaged properties, with some info about who is the mortgage holder and the property value vs the unpaid balance. Do you think you could help me out on this?

Seeking a marketing automation specialist to connect Zoho or a custom CRM to SmartLead.AI and Clay via API. The role involves setting up API connections to trigger campaigns and automate workflows. Experience with Zoho CRM and API integration is essential. The project is part-time and expected to last 1 to 3 months.

Hi, ive started a chat via text that people subscribe to to receive weekly messages and i wanted to add a feature that they could text the number and an ai chatbot would give an answer solely pulling information from a book I wrote and nothing else. I played around with zapier and chat gpt for a while, but the answers were always terrible at best. Looking for someone who can put together a better product, so the answers can be spot on. I've been using Zapier's Copilot so far and the answers, as I said, are quite poor.

Project Overview

We are looking for an experienced Web Scraping / Data Extraction Freelancer to scrape a list of Travel Advisors from a specific website (link will be provided upon hiring/discussion).
The target data needs to be extracted, cleaned, and organized into a structured format (CSV/Excel) so we can utilize it for our marketing and outreach efforts.

Scope of Work & Data Fields Required

You will be responsible for scraping all available Travel Advisor profiles on the target site and populating a clean spreadsheet containing the following fields for each entry:
Full Name
Agency Name
Location (City, State/Country)
Email Address
Phone Number
Any additional relevant profile details available (e.g., agency name, specializations, if present)

Key Deliverables

A fully scraped, deduplicated, and properly formatted dataset in Excel (.xlsx) or CSV format.
High data accuracy (ensuring email formats are correct and fields aren't misaligned).
(Optional) The python script or code tool used for the extraction in case re-scraping is needed in the future.

Requirements & Skills Needed

Proven experience in web scraping, data extraction, and lead generation.
Expertise with scraping tools/frameworks (Python, BeautifulSoup, Scrapy, Selenium, Puppeteer, or Octoparse/ParseHub).
Ability to handle dynamic content, pagination, or basic anti-scraping protections if applicable.
Attention to detail—data must be clean, correctly columned, and formatted.

To Apply

Please submit your proposal with:
1. Examples or brief descriptions of similar web scraping/directory extraction projects you’ve completed.
2. The primary tools or programming languages you plan to use.
3. Your estimated turnaround time for scraping a directory dataset once the link is provided.

Description:
We are looking for a freelancer to extract marketing agency data from Clutch.co.

Required fields:

Agency Name
Location
Number of Employees
Website URL


Source URL:
(link removed)

Expected output:

CSV file
One row per agency
Clean and deduplicated data

Requirements:

Experience with Web Scraping
Python, Playwright, Selenium, or similar tools
Ability to deliver accurate and complete data

Project Type:
One-time project
Have you scraped Clutch.co before?