I work as a project manager for a small group - part time. This is a group of Contract Specialists that complete a number of contract actions on a daily basis. Every month we have a daunting task of manually creating reports - it's awful. Its inefficient and time consuming. I started working with chat GPT to develop an automated system. It created a mockup, prototype farmwork that was awesome, but now it's getting way over my head in coding stuff I know nothing about. I'm lost.

OVERVIEW:DailyQuotes Inc. is seeking an elite, independent Python developer for immediate contract work to finalize a high-performance desktop market tracking utility.THE CURRENT STATUS:The complete front-end user interface layout, 14-column silver trading grid, custom user check-boxes, text-resizing components, and standard Windows setup wizard installer are 100% completed and structurally stable. You are NOT building this app from scratch. You are inheriting a pre-built visual code shell. A strict corporate Non-Disclosure Agreement (NDA) must be digitally signed before source files are shared.TECHNICAL OBJECTIVES & RE-ARCHITECTURE:Multi-Broker Connection Repair: Take the existing code frame, analyze the background network scripts, strip out legacy sandbox variables, and establish active, flawless multi-threaded data connections to stream real-time data from THREE distinct brokerage services based on user configuration: Alpaca Securities (WebSockets), Charles Schwab (OAuth2/API), and Interactive Brokers (IB API / TWS Gateway integration). The milestone will only be released when the 14 rows display real-time flashing stock quotes on the client’s workstation out of the box.Visual Asset Patch: Modify the compiled application asset properties to change the desktop execution shortcut icon and main window display logo from its current theme color to corporate Green.Audio Engine Sync: Wire the internal text-to-speech engine to track active column variables, ensuring that when the user adjusts the speed intervals and checks the "Speak" boxes, the desktop speakers dictate the tape cleanly without latency or system lag.Legal Intercept Gate: Hardcode an un-bypassable Financial Risk Disclaimer pop-up box that blurs the application frame on initial boot, forcing the user to check a mandatory terms agreement box to unlock the utility.THE RETAINER CONTRACT BONUS:This is a 2-Milestone fixed-price delivery contract budgeted at exactly $1,200.00 total. The exact millisecond the core utility runs smoothly on autopilot, the main contract will close, and DailyQuotes Inc. will immediately issue a recurring, ongoing Monthly Maintenance Retainer of $150.00 per month for a hard cap of 4 hours of on-call technical support per month. If zero hours are used, the full $150.00 is still paid to keep our organization on your active priority client list.REQUIRED EXCELLENCE:Deep mastery of Python, asyncio, low-latency multi-threading, and financial exchange APIs (specifically Alpaca, Schwab API, and IBkr API). Independent specialists only. No agencies.Please reply with your direct availability to begin architectural review this week. Thank you.

Python Developer Needed for Custom Local Document Automation & Quote Generator Job Description: I am looking for an experienced Python developer to build a custom, local desktop tool (or simple local web app) to automate my daily product quotation workflow. The Problem: I generate custom quotes for products daily, which currently takes me about 30 minutes per quote. I have an archive folder of over 2,500 past quotes ([PDF and Word versions or each quote) containing detailed technical product descriptions, images of the product, price and a specific layouts that I want to use. What the Tool Needs to Do: User Interface: Provide a simple, clean interface ~ local on my Windows PC or browser based, whatever is easiest (I prefer m local directory) but I don't really care ... that does the following: First ... using the example quote attached, create a similarly styled template which the following information can be "pulled into". 1. User inputs Customer Name, Company Name, Current Date, and Quote Number. 2. User inputs part number(s) that they want to add into the quote template. 3. SW searches & extracts from my archive folder of 2,500+ past quotes ~ finds the MOST RECENT quote with the matching part number(s) based on the past quote date, 4. SW extracts product information and ports into our new WORD quote template. 5. SW populates extracted info along with new customer details into WORD template that I currently use. Note that there is a product image in the old quotes that will have to be pulled over. Required Skills: -- Python (strong scripting and text processing) -- PDF/Word parsing and generation (e.g., pdfplumber, python-docx, ReportLab) -- Simple GUI development (Streamlit, PyQt, or Tkinter) Please reply with a brief description of a similar document parsing or automation tool you have built.

OVERVIEW:DailyQuotes Inc. is seeking an elite, independent Python developer for immediate contract work to finalize a high-performance desktop market tracking utility.THE CURRENT STATUS:The complete front-end user interface layout, 14-column silver trading grid, custom user check-boxes, text-resizing components, and standard Windows setup wizard installer are 100% completed and structurally stable. You are NOT building this app from scratch. You are inheriting a pre-built visual code shell. A strict corporate Non-Disclosure Agreement (NDA) must be digitally signed before source files are shared.TECHNICAL OBJECTIVES & RE-ARCHITECTURE:Multi-Broker Connection Repair: Take the existing code frame, analyze the background network scripts, strip out legacy sandbox variables, and establish active, flawless multi-threaded data connections to stream real-time data from THREE distinct brokerage services based on user configuration: Alpaca Securities (WebSockets), Charles Schwab (OAuth2/API), and Interactive Brokers (IB API / TWS Gateway integration). The milestone will only be released when the 14 rows display real-time flashing stock quotes on the client’s workstation out of the box.Visual Asset Patch: Modify the compiled application asset properties to change the desktop execution shortcut icon and main window display logo from its current theme color to corporate Green.Audio Engine Sync: Wire the internal text-to-speech engine to track active column variables, ensuring that when the user adjusts the speed intervals and checks the "Speak" boxes, the desktop speakers dictate the tape cleanly without latency or system lag.Legal Intercept Gate: Hardcode an un-bypassable Financial Risk Disclaimer pop-up box that blurs the application frame on initial boot, forcing the user to check a mandatory terms agreement box to unlock the utility.THE RETAINER CONTRACT BONUS:This is a 2-Milestone fixed-price delivery contract budgeted at exactly $1,200.00 total. The exact millisecond the core utility runs smoothly on autopilot, the main contract will close, and DailyQuotes Inc. will immediately issue a recurring, ongoing Monthly Maintenance Retainer of $150.00 per month for a hard cap of 4 hours of on-call technical support per month. If zero hours are used, the full $150.00 is still paid to keep our organization on your active priority client list.REQUIRED EXCELLENCE:Deep mastery of Python, asyncio, low-latency multi-threading, and financial exchange APIs (specifically Alpaca, Schwab API, and IBkr API). Independent specialists only. No agencies.Please reply with your direct availability to begin architectural review this week. Thank you.

Title: Data Enrichment Engineer Job Description: We need an experienced Data Engineer to enrich a large database of B2B records with missing emails, phone numbers, names, titles, and LinkedIn profile URLs. You will: • Build a reliable enrichment pipeline using APIs from ZoomInfo, LinkedIn Sales Navigator (or partners like Evaboot), and Salesgear. • Handle CSV processing, deduplication, fuzzy matching, confidence scoring, and email/phone validation. • Implement sampled manual QA process and deliver clean, enriched data + reusable scripts. Requirements: • Strong Python or .NET/C# skills. • Proven experience with sales intelligence APIs • Experience processing large datasets (20k+ records). • Attention to data quality and compliance. Please share similar past projects and list which provider APIs you have implemented.

What I Need Help With I have already set up my Raspberry Pi 5 and microscope camera. I am looking for someone to help implement the software pipeline for my project. Specifically, I need assistance with: Setting up and organizing the Python project structure. Use machine learning to be able to identify changes in morphology for each group over time (16 different experimental groups = 16 analysis folders to be compared to each other through ML) Building an automated workflow that processes microscope images using a custom-trained YOLO (Ultralytics) model. Running object detection on microscope images of Microcystis aeruginosa colonies. Extracting quantitative measurements from each detected colony, including colony count, area, equivalent diameter, circularity, and density. Automatically exporting all measurements into a CSV or Excel spreadsheet, with one row of data per image, and each piece of data being tracked based on which group it was taken from. Saving annotated images showing the YOLO detections for later review. Writing clean, modular, and well-documented Python code Troubleshooting any software or integration issues that arise during development.

**Project Overview:** I am looking for an expert developer to build a lightweight desktop stock ticker application (Windows/macOS preferred) where the MAIN focus is high-utility, fully customizable AUDIBLE alerts. I want to monitor the markets by ear without constantly staring at my screen. The app will feature a customizable "Quote Builder" layout running on fast user-defined refresh loops, but the sound engine is the absolute priority of this project. **Core Audio Requirements (The Main Point):** * Event-Driven Sound Profiles: I need to assign distinct, custom text-to-speech (TTS) speeds, pitches, or triggers based on user-defined price movements. * Directional Audio Logic: Distinctly different tone pitches or speech profiles for "Up" ticks versus "Down" ticks so I can instantly hear market direction. * Speech Profiles: A drop-down menu to toggle between "Standard Mode" (reads full labels: "Tesla 100, up 2, bid 99...") and "Pro Mode" (strips all labels for high-speed tracking: "TSLA, 100, up 2, 99..."). * Global Panic Mute: Hitting the Spacebar or a dedicated hotkey must instantly mute/unmute all active audio feedback immediately. * API Key Settings & Data Feeds: The app must use a "Bring Your Own Data Feed" architecture. It must feature a configuration settings screen where users input their personal, API credentials (keys and tokens) to feed data into the ticker. * Brokerage Dropdown Selector: The UI must include a simple drop-down menu allowing users to choose which data provider or brokerage connection to activate (e.g., [Dropdown: Alpaca Markets, Polygon.io, Interactive Brokers, Yahoo Finance]). The developer must build modular data adapters for these connections. **Data & Interface Requirements:** * Custom Quote Builder: Ability to save layout templates choosing from fields like Symbol, Last Price, Up/Down, Bid/Ask Size, Day High/Low, Open, and Close. * Fast Polling Loops: Drop-down selector for data intervals per ticker: 1 second, 5 seconds, 30 seconds, 1 minute, or 5 minutes. * Multi-Monitor Support: Global hotkeys to switch saved templates instantly without needing the app window to be in active focus. * Ticker Looping: Supports inputting a single ticker or a comma-separated list to cycle through multiple stocks on the interval loop. **Budget & Contract Setup:** * Contract Type: Fixed-Price * Total Project Budget: $3,000 (To be broken into milestones upon signing an NDA) ⚠️ CRITICAL: You must start the very first word of your cover letter/proposal with the word "TICKER" to prove you are a human and not an automated bot. If your proposal does not start with the word "TICKER", it will be instantly declined without review. Please reply by explaining your experience with asynchronous programming, audio-based desktop systems, or handling high-speed financial APIs (like Alpaca or Polygon.io). Selected candidates will be asked to sign an NDA before receiving the full requirements document.

We are hiring a senior scraping engineer to join an experienced team building a real estate data platform. This is not a new build starting from scratch. We are approximately 90% of the way to launch, with the core platform already in place and the team pushing through the final stage of development. We are a small team, which means every hire matters. We are looking for an A player who can take ownership of data acquisition, solve difficult problems, and help us get the product across the finish line. The Role You will own data acquisition for our platform. Your primary focus will be building, maintaining, and improving our scraping systems. You will not own frontend development, billing systems, or the broader application backend. However, you must be comfortable with general backend development and understand how your scraping systems connect to the rest of a production application. You may need to assist with integration work, troubleshoot issues across system boundaries, and make backend changes related to the reliable delivery of scraped data. Your job is to: -Scrape the required source data. -Build and maintain reliable production scrapers. -Validate the completeness and accuracy of the results. -Deliver data using the agreed schema and system architecture. -Work with the backend team to integrate the data successfully. -Continue supporting and improving the scraping system after integration. We are looking for someone who genuinely enjoys scraping and is willing to work through difficult websites, changing page structures, browser issues, blocked requests, and incomplete data. This is not a role for someone who only builds simple, one-time scripts. We need someone who can own a production scraping system, diagnose failures independently, improve reliability, and keep the data flowing when source websites change. You will work closely with a Lead Backend Engineer who owns the broader backend platform. Scraping and data acquisition will remain your primary responsibility, but you will be expected to collaborate carefully on integrations and take responsibility for the ongoing performance of what you build. Responsibilities -Build and maintain Python scrapers. -Work with dynamic and JavaScript-heavy websites. -Build and maintain browser automation. -Diagnose blocked, failed, or incomplete runs. -Handle sessions, cookies, proxies, rate limits, and other access challenges. -Update scrapers when source websites change. -Validate data completeness and accuracy. -Prevent duplicate and missing records. -Add logging, retries, monitoring, and alerts. -Deliver data using an agreed schema and architecture. -Collaborate with the backend team on integration and troubleshooting. -Support scraping-related backend components when needed. -Document your work clearly. -Recommend better data-acquisition methods when appropriate. -Take long-term ownership of the reliability of the scraping systems you create. Required Experience -Strong Python experience -General backend development experience -Playwright, Selenium, Scrapy, or similar tools -Production web scraping -Browser automation -HTML parsing and structured data extraction -Proxy and session management -Retry and recovery systems -Monitoring unattended scrapers -Data validation -Docker -GitHub Experience with Cloudflare, CAPTCHA workflows, public records, APIs, Google Cloud Run, MongoDB, or BigQuery is helpful. What Success Looks Like -Scrapers run reliably without constant supervision. -Failures are detected quickly. -Missing and duplicate records are reduced. -Website changes are handled quickly. -Data is delivered accurately and on schedule. -Scraping systems integrate cleanly with the broader platform. -The backend team does not need to take ownership of maintaining the scrapers. -The systems you build remain understandable, supportable, and reliable over time. -We Are Looking for Someone Who enjoys solving difficult scraping problems. -Can work independently and diagnose issues without constant guidance. -Has experience maintaining production scraping systems. -Is comfortable working within a broader backend architecture. -Understands how to keep data pipelines reliable as websites change. -Takes care with architecture, documentation, testing, and maintainability. -Can communicate technical issues clearly and recommend improvements. -Takes ownership and pushes projects across the finish line.

Overview I am looking for an experienced Python developer to build a stand-alone desktop research application for futures trading strategy analysis. This is not an automated trading bot and does not require live trading execution. The purpose of this software is to replace manual backtesting and allow systematic research of Opening Range Breakout (ORB) strategies. The application will allow a trader to quickly test strategy variations, compare results, and identify robust parameters without manually running hundreds of backtests. Accuracy of results is the highest priority. Project Goal Build a desktop application where the user can: Select a futures market Load historical data Configure ORB strategy parameters Run single tests or multiple parameter combinations Analyze results Compare experiments side-by-side Save research results The software should be simple and user-friendly. Platform Stand-alone desktop application. Primary requirement: Windows Desired: macOS compatibility The user should not need: TradingView Excel FX Replay Coding knowledge The software should open like a normal desktop application. Supported Markets (Version 1) The architecture should support: Nasdaq Futures NQ MNQ S&P 500 Futures ES MES The system should properly handle: Tick size Tick value Contract specifications The design should allow additional futures markets to be added later. Data Requirements Historical Data Integration with: Databento API Requirements: 1-minute historical data User-selectable date ranges Ability to build higher timeframe candles from 1-minute data Supported research candles: 1 minute 3 minute 5 minute 10 minute 15 minute ORB Strategy Engine Standard ORB User can select: 1 minute 3 minute 5 minute 10 minute 15 minute opening range Dynamic ORB (Anchor ORB) User can select: 1 minute 3 minute 5 minute 10 minute 15 minute Logic: The first candle that closes outside the opening range becomes the new ORB anchor. The closing price of that candle becomes the reference level for entries. Entry Types Version 1 supports: Breakout entry Dynamic ORB anchor entry Stop Loss Testing User can test: 25% 33% 50% 66% 75% 100% Stop size is based on ORB size. Profit Target Testing The software must support testing multiple R targets: From: 0.5R to 10R In: 0.5R increments Example: 0.5R 1R 1.5R 2R etc. Risk Management Support: Fixed Dollar Risk Example: $100 $250 $500 Percentage Account Risk Example: 0.5% 1% 2% Filters ORB Size Filter User selectable: Minimum: 0.10% Maximum: 2.00% Day of Week Filter Allow testing: Monday Tuesday Wednesday Thursday Friday News Filters Option to exclude: High-impact economic news days FOMC days Federal Reserve Chair speech days Research Engine The software must support: Single Backtest Run one specific strategy configuration. Multi-Variable Testing Allow combinations of: Market ORB duration ORB size Entry type Stop size Profit target Day filters News filters Example: Test: 10 ORB sizes 6 stop sizes 20 profit targets Multiple markets Automatically generate and run experiments. Parameter Locking Important feature: The user must be able to lock certain parameters while testing others. Example: Lock: Entry type Risk model Optimize: ORB size Stop Target This prevents unnecessary over-optimization. Results Dashboard Display: Performance Metrics Net Profit Profit Factor Expectancy Win Rate Total Trades Average Winner Average Loser Maximum Drawdown Largest Winning Streak Largest Losing Streak Charts Required: Equity Curve Drawdown Curve Experiment Comparison Allow side-by-side comparison. Example: Strategy A vs Strategy B Compare: Parameters Profit Factor Expectancy Drawdown Trade count Win rate Saving Research Users should be able to: Save experiments Reopen experiments Save notes Technical Preferences Preferred: Python backend Open to developer recommendations for: Desktop framework Database Architecture Experience preferred with: Financial applications Backtesting systems Time-series data Quantitative research tools Important Developer Qualifications Please have experience with: Event-driven backtesting Historical market data Avoiding look-ahead bias Accurate trade simulation Parameter optimization This project is research-focused. A simple candle backtester is not sufficient. Application Requirements Please provide: Examples of similar work GitHub or portfolio links if available Recommended technology stack Estimated timeline Fixed-price estimate Budget Expected MVP range: $4,000–$7,000 (depending on experience and recommended architecture) This project may expand into future versions after successful completion. Final Note The goal is to build a reliable research tool that allows systematic testing of futures strategies. The first version should prioritize: Accuracy Simplicity Ease of use Clean architecture for future expansion

Python Developer Needed – Claude API, PDF Processing & AI Automation I’m looking for an experienced Python developer to help me complete and troubleshoot an AI document-processing workflow. I have approximately 20,000 pages of OCR’d medical records that need to be processed using the Claude (Anthropic) API. The goal is to identify specific mental health evidence while ensuring every extracted finding includes the exact PDF filename and page number so it can be verified and used in court. Current Status * Claude API account is already set up and paid for. * PDFs are already OCR’d and page numbered. * I have an existing Python script that uploads documents and processes them, but it needs improvement. What I Need * Debug and improve the existing Python code. * Ensure page numbers and source filenames are always included. * Improve reliability and error handling. * Optimize processing of a large document set. * Help generate a final organized evidence list. Required Skills * Python * Claude (Anthropic) API or other LLM APIs * API integration * PDF/document processing * OCR workflows * Prompt engineering * Debugging and automation Experience working with legal, medical, or other large document collections is a plus. This is an urgent project, and I’m looking for someone who can start immediately. When applying, please include: * Similar projects you’ve completed * Your experience with Python and AI APIs * Your hourly rate * Your availability over the next couple of days I’m in Las Vegas