Property Search & Underwriting Script

@a4logic

Hello, Having successfully completed several web scraping and data management projects, I bring extensive skills and experience to the table. My proficiency in languages like Python and JavaScript, combined with hands-on utilization of necessary libraries such as Pandas, Requests, BeautifulSoup and Selenium make me a perfect fit for developing your Property Search & Underwriting script. Rest assured, I'm capable of working seamlessly with APIs and also building robust scrapers that respect rate limits and handling CAPTCHA challenges. Our commitment to excellence is highlighted by the fact that our company has emerged as one of the major web service providers in Pakistan. This wouldn't have been possible without our incredible dedication to client satisfaction and providing is always ready to turn dreams into reality. Equipped with these qualities, we at our Software will not only develop a clean, well-documented script that meets your specifications but also offer you a comprehensive setup guide alongside necessary files for easy maintenance. Our services extend even after the delivery with troubleshooting assistance provided for a considerable period. In addition to our ability to deliver precise results within specified timelines, we would add significant value to this project by providing an example CSV, JSON, and underwriting worksheet along with a short demo video or written walkthrough showing how the tool operates. Trust us Thanks!

@SBITServices

Hi, I will develop a Python script using Pandas, Requests, BeautifulSoup, and Jupyter for property search and underwriting. The script will scan various U.S. property data sources, apply customizable filters, automatically underwrite listings, and provide downloadable outputs for easy integration with your CRM. I will ensure clear documentation, editable assumption cells, and a user-friendly setup guide. Let's discuss further in chat. Regards, Sai Bhaskar

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Script to Scan U.S. Property Data Sources for Deals ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and noticed you're looking for a script to scan U.S. property data sources efficiently. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in real estate data analysis. I will create a well-documented script that scans MLS feeds, Zillow, Redfin, and public tax records, allowing you to set and change filters like location, price, and property type in real time. ➡️ Why Me? I have 5 years of experience in creating automation scripts, especially for real estate data analysis. My skills include data scraping, API integration, and data processing. I have a strong grip on Python and JavaScript, which will ensure a smooth and efficient solution for your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you! ➡️ Skills & Experience: ✅ Python Programming ✅ JavaScript ✅ Data Scraping ✅ API Integration ✅ Real Estate Analysis ✅ Data Processing ✅ Spreadsheet Automation ✅ JSON Handling ✅ Documentation ✅ Troubleshooting ✅ Time Optimization ✅ User-Friendly Interfaces Waiting for your response! Best Regards, Zohaib

@WebTechDesignBG

Woah Hello, It sounds like you need a robust script that can sift through various U.S. property data sources to quickly identify deals that fit your criteria. I’d approach this by setting up a script that can dynamically adjust filters like location, price, and property condition. Using Python with libraries like Pandas and BeautifulSoup, I can ensure we pull the right data efficiently. With 7+ years of experience in web scraping and API integration, I can create a system that not only finds properties but also performs detailed underwriting calculations. This includes generating financial metrics like NOI and cap rate, all while packaging the results neatly for your CRM. I’ll make sure the script is well-documented, and provide a setup guide to help you get started easily. Best regards, Ivan Mandinski

@umer6316326

Hi, I’m writing this bid myself and feel confident in delivering a robust, clean, and well-documented script tailored to your property search and underwriting needs. I’ve worked extensively with web scraping, API integrations, and financial modeling, especially using Python and JavaScript, so I can efficiently build your tool that dynamically filters properties and performs real-time underwriting with editable assumptions. I’ll ensure the script integrates smoothly with major data sources, respects rate limits and captchas, and outputs both JSON and spreadsheets for seamless CRM import. I will also provide detailed setup instructions, sample data outputs, and a guided walkthrough video to make adoption easy. After delivery, I’m happy to support troubleshooting and enhancements to guarantee smooth operations. Let’s start by defining your primary metro area and any specific data sources you prefer so I can get an accurate head start. I anticipate completing the base script reliably within three weeks. Which metro areas and specific property data sources would you like prioritized for initial integration? Best regards,

@mohjib092

I can build a Python-based property scanner and automated underwriter with live filters, CSV/JSON outputss, backed by 5+ years of experience in real estate data automation and API/scraping solutions, including setup and troubleshooting support

@eliaa

Hello, I am reaching out from Smart Sols, a software development company with over 9 years of experience in full-stack development. We understand you need a clean, well-documented script to scan major U.S. property data sources like MLS feeds and Zillow for property search and underwriting purposes. We have strong expertise in backend development using PHP and Laravel, ensuring robust data integration and processing. Our team emphasizes code clarity and documentation, which aligns perfectly with your requirements. We can deliver a scalable and maintainable solution tailored to your needs, with possible integration of APIs and efficient data parsing techniques. We are confident in delivering this project on time with high quality. Looking forward to discussing your project details and next steps.

@elishadiah326

Hi, this project is really about building a dependable acquisition tool, not just a scraper. The key is combining property discovery, buy-box filtering, rent-comp underwriting, and export-ready outputs into one workflow that is fast enough to use daily and simple enough for you to maintain. I’d recommend Python for this build because it is the cleanest fit for property data collection, underwriting logic, CSV/JSON export, and future tweaks in Jupyter. My approach would be to structure the tool in four layers: data ingestion from the chosen sources, filter engine for your buy box, underwriting module for NOI/cap rate/cash-on-cash/IRR, and export layer for spreadsheet + CRM-ready JSON. I’d also keep assumption inputs editable so vacancy, expenses, financing terms, and exit cap can be adjusted without touching the core logic. What gives me confidence here is my experience building structured data and workflow tools where API/scraping logic, clean calculations, and maintainable code all need to work together reliably. My focus would be to deliver something practical: clear source code, setup help, example outputs, and post-delivery troubleshooting so you can actually run it with confidence. If you want this built as a clean, usable acquisition engine rather than a fragile script, I’d be glad to discuss the next step. Best regards, Diah

@ShaikhAneesa

Hi there, I’ve carefully reviewed your project and understand you need a system that can scan real estate data sources, filter properties based on your buy box, and automatically underwrite each deal with key financial metrics, producing structured outputs for analysis and CRM integration. My approach begins with building a Python-based pipeline that retrieves listings via APIs where available and compliant scraping where necessary. I will design flexible, real-time filters so you can adjust location, price range, property type, and distress status without changing the core code. Next, I will implement an underwriting module that enriches each listing with rent comps and calculates NOI, cap rate, cash-on-cash return, and IRR. Editable assumptions such as vacancy, expenses, financing terms, and exit cap will be included so you can easily run scenarios and refine investment decisions. The output will be delivered as a clean spreadsheet (CSV/Excel) and a structured JSON file suitable for CRM ingestion. The script will be optimized for performance to process multiple properties efficiently within your time constraints. Finally, I will provide well-documented source code, setup instructions, sample outputs, and support during setup and troubleshooting to ensure smooth execution. How would you like to prioritize data sources; should we start with a specific provider or design the system to aggregate from multiple sources from the outset? Warm regards, Aneesa.

@koolvishruth

Hi Sir, I am webscraper with 8 years of experience.I will build python script.I have a question for you Do you already have an API key for a data provider (like Attom or RealtyMole), or would you like me to build the initial version using a "Scraper" approach for public-facing sites? Please message through chat

@jayprakashyadav

Hello! I'm Jay, a versatile and experienced developer with a whole toolbox of skills that make me a great fit for your property search and underwriting scripting project. While I'm mostly specialized in Mobile App Development and Automation, I bring years of experience in web development, API integrations and web scraping using Python, JavaScript, Node.js. Your project requires precise filtering, data-fetching from various sources (MLs, Zillow, etc.), thorough underwriting calculations, all wrapped up in an easy-to-use interface - all of which boil down to automation with correct assumptions. Having developed similar projects in the past using Pandas for data processing, Requests + BeautifulSoup/Selenium for scraping & dealing with rate limits, JSON manipulation & exporting results into spreadsheets with Python gives me an important edge. Plus your preference for Python (Pandas, Requests, BeautifulSoup or Selenium) or JavaScript with Node aligns perfectly with my comfort zone ensuring I can deliver a quality product while reducing the learning curve. I will also include well-commented code and setup guides to ensure easy maintenence along with a thorough demonstration of the script in action Thanks, Jay

@abhisaini0188

Hi, This is exactly the kind of data-driven real estate automation tool I’ve built before. I can develop a Python-based script (Pandas + APIs/scraping) that: Scans property sources (MLS alternatives, Zillow/Redfin/public data) Applies real-time filters (location, price, distress status, etc.) Automatically underwrites deals (NOI, cap rate, cash-on-cash, IRR) Exports results to CSV + JSON + editable underwriting sheet I’ll ensure clean, well-documented code, rate-limit-safe scraping, and fast execution (<2 mins). Included: Full source code + setup guide Example outputs (CSV/JSON/Excel) Loom walkthrough Post-delivery support for setup & troubleshooting I can also help you run and customize it easily (even if you’re new to tools like this). Let’s build a powerful deal-finding system. With Regards!

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. I have 10+ years of experience in mobile and web app development, including expertise in creating automated scripts and data scraping tools. My strong background in Python and JavaScript, along with proficiency in libraries like Pandas and BeautifulSoup, positions me well to deliver a robust property search and underwriting solution that meets your specifications. I will ensure the script can scan various U.S. property data sources effectively and allows real-time adjustments to your filters. It will process underwriting calculations swiftly and provide the outputs in both downloadable formats. Clear documentation and a setup guide will be included for ease of use. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m keen to understand a few details to ensure the best approach. Could you clarify: 1. Are there specific MLS feeds or APIs you prefer to include? Are there specific MLS feeds or APIs you prefer to include? Let’s discuss over chat! Regards, Arpit Jaiswal

@hassannaweed4

With your Property Search & Underwriting Script project, I believe I can create a solution that exceeds your expectations. Armed with my extensive experience in Data Analysis, Python, and Web Scraping, I am confident in my ability to craft a clean, well-documented script that will pull data from various property sources efficiently and effectively. Whether it's the MLS feeds, Zillow, Redfin API or even public tax records, I can ensure that the script will gather all necessary information. What sets me apart is my proficiency in not just collating the data but also analyzing it. This means that not only can I help you filter out potential properties based on your parameters in real-time but I can also swiftly underwrite them by pulling rent comps and calculating projected NOI, cap rate, cash-on-cash flow and simple IRR. Functionality aside, I also prioritize ease-of-use. As an experienced software engineer with a Master’s in Software Engineering specializing in big data and automation workflows, I understand how important it is that you're able to manipulate assumptions on the fly for fine-tuning scenarios. All said, I look forward to collaborating with you to revolutionize your property search and underwriting process by bringing advanced python skills to work. The deliverables you'll receive will be meticulous including full source code with clear comments to enhance maintainability over time!

@chandankandar007

As a seasoned full-stack developer with over 13 years of experience, I am well-versed in the key programming languages and tools necessary for this property search and underwriting project. My expertise in Python (with Pandas, Requests, BeautifulSoup or Selenium) and my familiarity with JavaScript (Node.js) with their respective libraries goes hand-in-hand with your technology preferences for this project. Additionally, I have extensively worked on API integrations, data analysis as well as system architecture, all valuable skills for delivering an efficient script that meets your needs. Throughout my career, I have built various web applications and backend services from scratch. This has equipped me to understand the importance not only of clean code but of clear documentation and strong testing methodologies as well. You can expect a well-documented script where lines are commented thoroughly which would be beneficial if you ever need to maintain it yourself in the future.

@rbtech1984

Hello There!!! ★★★★ ( Automated property search and underwriting tool for U.S. real estate ) ★★★★ I understand you need a script that scans MLS, Zillow, Redfin, and public records to find properties matching your buy box, then underwrites each deal automatically with rent comps, NOI, cap rate, cash-on-cash, and IRR. Filters must be editable in real time, and outputs delivered as CSV, JSON, and spreadsheet, with easy tweaks and assumptions. ⚜ Property search across multiple U.S. data sources ⚜ Real-time adjustable filters: location, price, type, distressed status, co-living potential ⚜ Automated underwriting calculations (NOI, cap rate, cash-on-cash, IRR) ⚜ Export results in CSV, JSON, and Excel-friendly formats ⚜ Editable assumption cells for vacancy, expenses, financing, exit cap ⚜ Clear, well-documented source code with setup guide ⚜ Troubleshooting support and walkthrough for setup I have built Python and Node.js scraping/analytics tools for real estate before, combining APIs and scrapers with Pandas for fast calculation. I’ll use modular code, proper rate limiting, and provide a Loom walkthrough. Happy to get your tool live and reliable quickly. Warm Regards, Farhin B.

@samirsauma

Hi , Good morning! I am an expert mobile developer with skills including Web Scraping, PHP, JavaScript, Python, Data Analysis, API Integration, Node.js and Pandas. Please contact me to discuss more regarding this project. Eager to hear your feedback

@Tanmoy236

Warm greetings! I specialize in building real estate data scraping and automated underwriting systems using Python/Node.js with 9+ years of experience in data pipelines, APIs, and investment analytics tools. Here's how I can help: * Build scalable scraper/API connectors for MLS, Zillow, Redfin, and public records (rate-limited, compliant) * Implement real-time buy-box filtering (location, price, distress, property type, condition) * Automated underwriting engine (NOI, cap rate, cash-on-cash, IRR) using Pandas * Export results to CSV, JSON, and CRM-ready structured payloads * Editable assumptions module (vacancy, expenses, financing, exit cap) Approach: design modular pipeline → data ingestion layer → filtering engine → underwriting calculator → export + validation testing. I also provide setup support and troubleshooting during deployment. Quick question: do you already have API access for MLS/third-party data sources, or should the system rely primarily on public + scraped datasets?

@jushuamurillo98

Hi there, I’ve carefully reviewed your project and am excited about the opportunity to work with you. With 7 years of experience in Python, Node.js and advanced property data automation, I specialize in building intelligent acquisition tools that surface investment-grade deals and run instant underwriting. I am confident I can solve your need for a clean, flexible script that scans MLS alternatives, Zillow, Redfin and public records while producing fast, accurate financial outputs. Here’s my approach: Build modular data collectors using APIs or scrapers with rate limit handling Create an underwriting engine calculating NOI, cap rate, cash-on-cash and IRR with editable assumptions I am available to start immediately and aim to deliver a working prototype within 7 days. Additional instructions / notes (optional): Full documentation and walkthrough will be included Troubleshooting and setup support provided Thanks, Jushua