Quantitative Developer for Market Structure Engine

@ykarora26

Experienced Python developer with a strong background in market data processing and algorithmic trading systems. I understand the need for a custom non-print market structure engine utilizing Interactive Brokers Time & Sales data for AI-driven analysis. Proficient in Python, Interactive Brokers API, and real-time market data processing. Can you provide more insight into the specific AI integration requirements for this project? Regards, Yogesh Kumar

@axiomswb

Architecting your Non-Print engines... You need a multi-threaded Python backend to ingest zero-latency IBKR Time & Sales data and manage 200 independent LineBreak structures in-memory. Here is my execution plan: Tick Ingestion: Build an async IBKR WebSocket listener to process raw ticks into Non-Print events, updating the 200 virtual arrays in-memory. Agent Negative Logic: Wire your exact classification formulas (Compression, Expansion) into the event loop, logging state transitions into TimescaleDB. AI-Ready UI: Expose synchronized states via WebSocket endpoints for your dashboard. For your $30 budget, I will deliver Phase 1: A complete Technical Blueprint, Database Schema, and Python Class Structure for this architecture. Quick question: Should live states broadcast on every single tick, or batched every 500ms to conserve CPU?

@krupnovdenis

Hello! We can provide an external Python team to build this market data research platform. 1. Are you open to working with an external contractor or team for these tasks? 2. Which parts need to be covered first: data ingestion, Line Break engines, classification, or dashboard? — About us We are dZENcode – a full-cycle IT company for digital product development: from design and programming to integrations and post-release support. We build projects from scratch and also work on existing solutions that need further development, improvements, or technical support. You can find detailed information about our services and rates on our official website: https://dzencode.com. Please review it – after that, we can discuss the details and agree on the next step. ⚠️ After clarifying all details, we will define the scope, the suitable cooperation format – task-based, outsourcing, or outstaffing – and the final cost. Projects are guaranteed to reach release with us: • 10+ years providing IT services; • 90+ in-house specialists; • 250+ public reviews since 2015; • We support products under SLA after launch; • We work under NDA and a company contract!

@talkwaqar

I'd build the Bid and Ask Non-Print engines as two fully independent event streams off the IBKR Time & Sales feed, then feed both into 200 in-memory Line Break data structures (1 through 100 resolution, per side) with zero chart rendering. Your point about modeling liquidity absence rather than price movement is the part most bidders will miss, and it's exactly why the Non-Print event bus has to be the core, not the charts. How I'd structure it: 1. One async ingestion layer (ib_insync) writing raw Time & Sales to TimescaleDB, with the Non-Print detection (zero-print levels, voids, gaps, persistence) computed on the same pass. 2. A single shared event bus so all 100 Line Break resolutions per side subscribe to one Non-Print stream instead of recomputing per engine. This is what keeps CPU flat while 200 engines update. 3. Your provided classification formulas applied per engine, scores stored as state, exposed over JSON/WebSocket/API for the future AI agents. Answers to your questions: 1. Trading systems: my background is event-driven, high-throughput data platforms (real-time ingestion, classification, replay) rather than retail bots. Architecture is the transferable core here. 2. IBKR: I'd use ib_insync for the Time & Sales subscription and historical pulls. Happy to start against a paper account. 3. Custom chart construction: Line Break as a pure data structure (each new break appends a state row, reversal logic gated by the N-line threshold) is the right model, not a plotting library. 4. Event-driven market data: yes, this is the part of the brief I'm strongest on, single producer, many subscribers, backpressure-aware. 5. Tick data storage: TimescaleDB hypertables on the raw Time & Sales, with continuous aggregates for the structural states and replay. 6. Timeline: see below. 7. Cost: $22 for the first milestone, consistent with my bid. Given the real scope (200 engines, replay, dashboard, AI output), I'd phase it so you get something verifiable fast: 1. Days 1-3: IBKR ingestion + Bid/Ask Non-Print engines + TimescaleDB schema. 2. Days 4-5: 200 Line Break engines in memory, your classification formulas wired in. 3. Days 6-7: single rendered main chart + 200 lightweight status panels (color + score), plus the JSON/WebSocket output layer. Done = live IBKR ticks produce independent Bid and Ask Non-Print events, 200 Line Break states update in memory, and the 200 panels reflect their current scores, with no per-engine chart rendering. Do you want the first milestone scoped to ingestion plus the two Non-Print engines, or should the 200 Line Break structures be in that same first delivery? Waqar

@ayesha86664

Hi there! This project needs more than a trading bot, it requires a proper market microstructure data engine that can handle continuous Time & Sales processing without breaking under load. If the architecture is weak, the 200 Line Break engines and real-time updates can easily become slow or unstable. I am a Python backend developer with strong experience in real-time market data systems, event-driven architecture, and API integrations like Interactive Brokers. I have worked with PostgreSQL/TimescaleDB for tick-level storage and built streaming pipelines using WebSockets and asynchronous processing for financial data systems. I also understand designing scalable data structures for ML/AI-ready pipelines and historical replay systems. My approach will start with designing a clean event-driven architecture for IBKR Time & Sales ingestion. Then I will separate and build optimized Bid/Ask non-print data engines with in-memory efficiency. After that, I will implement your 200 Line Break data structures with proper state management and minimal resource usage. Finally, I will add a lightweight dashboard, API/WebSocket layer, and database design for storage and replay. check our work https://www.freelancer.com/u/ayesha86664 Are you already using IBKR TWS or IB Gateway for live data streaming? Let me know if you’re interested & we can discuss it. Best Regards Ayesha

@ammarahmed20

Drawing from my ?+ ????? of experience in delivering full-stack platforms, SaaS products, automation systems, and AI agents with a focus on production, I'm confident I can build your custom market structure engine to the exact specifications you've laid out. My strongest skills in Python, API integration, and MySQL align seamlessly with the needs for your project's data processing, algorithmic trading systems, WebSocket architecture, and database storage. Further amplifying my skill set is my understanding of various AI technologies such as machine learning (ML), an attribute that is highly preferred for this project. One aspect that I believe sets me apart is my keen attention to detail and prioritization of efficiency. I am acutely aware of the importance of accurate line break construction for your proprietary charts in creating reliable datasets that the classification engines will depend on. Secondly, my appreciation for project costs and optimization will guarantee we stay well within the budget without compromising deliverables- an invaluable trait when dealing with potentially CPU/memory heavy charts like this one.

@chandibraheem58

Hi, Hi, This project centers on building a market structure analysis platform where data accuracy, event processing, and scalable architecture are more important than visual charting. Separating the Bid and Ask Non-Print engines while maintaining independent Line Break data structures is essential for supporting the downstream classification and AI workflows you've described. The implementation can be structured around real-time data ingestion, event-driven processing, PostgreSQL for historical storage, and an API layer for future AI integration. The dashboard will focus on presenting structural states efficiently while keeping the processing engines independent of the visualization layer. Open to reviewing the technical scope and discussing the implementation strategy. Best regards, chand

@hoangvanp

Hi, I can develop a proprietary market structure research and analysis platform using Interactive Brokers Time & Sales data. The system will generate independent Bid and Ask Non-Print Data Engines, construct Line Break charts accurately, and apply provided classification formulas to each engine for liquidity modeling. I have experience with Python, Interactive Brokers API, real-time market data processing, and custom chart construction. For this project, I would start by processing live Time & Sales data, building separate Bid and Ask non-print datasets, and developing 200 Line Break data engines internally without visual rendering to minimize CPU and memory usage. A key challenge is ensuring accurate Line Break chart construction for downstream classification. I address this by focusing on maintaining data structures internally and updating them efficiently in memory and/or database form. I will provide fully documented Python code, database schema, real-time data ingestion, Line Break engines, classification integration, dashboard UI, historical replay capability, and transfer ownership of the source code upon completion. Let's discuss the details via chat. Regards,

@tyronet2

---PROPOSAL--- You’re building a real-time market microstructure engine that processes IBKR Time & Sales into bid/ask non-print liquidity models with 200 internal Line Break data engines and a live dashboard. I’ve built event-driven, real-time data systems at Marin Software using Python + async pipelines + PostgreSQL/Redis, where we processed high-frequency streams and maintained stateful analytical models for downstream ML and visualization layers. For this, I’d design a Python async architecture with IBKR WebSocket ingestion, TimescaleDB for tick storage, and in-memory state engines for the 200 Line Break structures. Each engine runs as a lightweight state machine updated per tick, not rendered charts. FastAPI + WebSocket layer will stream classification states to a React dashboard (single main chart + 200 status panels). System optimized for continuous low-latency processing and future AI consumption via JSON streams. Timeline: 3–4 weeks for full system (ingestion + engines + storage + dashboard + replay layer). Quick question: do you already have IBKR market data subscription + sample Time & Sales feed for testing latency and structure?

@natanr28

As an experienced Python developer, specializing in the integration of APIs and trading system development, I am uniquely qualified to handle your needs for a quantitative developer for your market structure engine. My background includes extensive work with the Interactive Brokers API (IBKR), real-time market data processing, and timescaleDB, making me well-poised to construct the complex structural datasets you require - harnessing both the bid and ask non-print data engines with complete independence. I understand that your project is not a traditional trading bot setup; it requires careful construction of proprietary Line Break charts from the non-print datasets. With a thorough grasp of line break constructions and their significance in forming accurate data structures rather than visual indicators, I can help build 100 Bid Non-Print Line Break charts and 100 Ask Non-Print Line Break charts across different resolutions precisely addressing your requirements. Moreover, my approach to projects aligns perfectly with your needs. I start by meticulously understanding goals and project scope before planning architecture, workflow, and user experience. I look forward to using my skills, experience, and focused attention to detail to help craft a powerful market research and analysis platform to support your future AI-driven analysis and strategy development.

@Lazarone1

Hello, there.. Python dev for IBKR market data + event driven engine. Build bid/ask non-print systems, 200 internal line-break structures (no UI rendering), Timescale/Postgres storage, WebSocket pipeline, and real-time + replay + JSON/API output. Clean modular design for future AI layer. Need prior microstructure/tick data work. Can start ASAP, deliver MVP fast, then expand.

@anmolverma6

Hi, I have experience working with Python-based data processing systems, APIs, database integration, and real-time applications. Your project is particularly interesting because it focuses on market structure analysis and custom data engines rather than traditional trading bots. I can help design a scalable architecture for Time & Sales ingestion, Non-Print event processing, Line Break engine management, database storage, dashboard development, and future AI integration while keeping performance and maintainability in mind. I would be happy to discuss the architecture and implementation approach in detail.

@toqeer74

The challenge of constructing 200 independent Line Break data engines, while ensuring they are lightweight and solely data structures, highlights the need for a robust event-driven architecture. Implementing this efficiently requires advanced Python development and a deep understanding of market microstructure, particularly in handling Time & Sales data. My experience with Interactive Brokers API and PostgreSQL, along with expertise in multithreading and asynchronous programming, ensures a seamless data processing pipeline that minimizes resource usage. Expect the initial deliverable within 30 days. Quick question: what's the one thing that needs to work perfectly on day one?

@hectorortiz26

Hi, I noticed you're looking for a Python quantitative developer to build a market structure engine with algorithm development and API integration capabilities. I've spent over 10 years building fintech solutions and custom backend services using Python, FastAPI, and MySQL. My work includes developing data-driven applications with clean architecture designed for reliability and performance. Here's how I'd approach this: - Review your existing market data sources and define the core algorithmic logic requirements - Build a modular Python engine with MySQL integration for efficient data storage and retrieval - Implement API endpoints and ensure the codebase is well-documented for future maintenance Could you share more details about the specific market structure calculations or trading signals you need the engine to process? I can start immediately and stay within your $20 budget. Send me a message here on Freelancer with any additional specifications, and we can move forward. Best regards, Hector R.

@lestery3

Hello! I'm excited about the possibility of collaborating on your innovative market structure engine. My background in software architecture, particularly in building robust Python systems, aligns perfectly with your project's objectives. I have significant experience in real-time market data processing, ensuring efficiency while processing vast amounts of information, similar to what you're aiming for with Interactive Brokers Time & Sales data. Having developed advanced event-driven architectures, I am well-versed in custom chart construction, which is crucial for your proprietary Line Break charts. I understand the importance of keeping these data structures both accurate and efficient, focusing on real-time updates that will be pivotal for your future AI integration desires. In my previous projects, I've crafted systems that effectively implemented multithreading and asynchronous programming to optimize performance while maintaining a lightweight footprint. I am adept at using PostgreSQL and TimescaleDB, ensuring that the database can handle both raw and processed data seamlessly. Lastly, I'd love to know what specific challenges you're facing regarding the AI integration to better understand how I can add value. What specific challenges do you foresee in integrating AI into the platform? Looking forward to potentially working together! Best, Lester

@johnk553

Hi, I’m interested in this project. I understand this is not a simple trading bot but a market structure research engine focused on real-time Time & Sales processing, custom data structures, and future AI integration. I can help build the architecture around Python, event-driven processing, API integration, database storage, and real-time updates. The approach of keeping LineBreak engines as internal data structures instead of rendering hundreds of charts makes sense for performance, and I can work with that design. I’m comfortable with building systems involving live data streams, WebSocket/API workflows, database-backed analytics, replay systems, and scalable backend logic. I’d like to review the IBKR data flow and your classification logic first, then implement the engines step by step with clean, maintainable code. Thanks!

@cliftonc20

Hello, this reads less like a generic Python build and more like a market data engine where the value is in how state, signals, and replay logic are structured. The real engineering risk is not model selection; it is preserving deterministic market-state reconstruction while keeping derived outputs usable in real time. I’ve built production analytics systems in Python where ingestion, feature generation, and downstream APIs had to stay cleanly separated under continuous data flow. The same discipline applies here, especially if the engine needs to support both research and live decisioning. The closest match is Dent-Cloud, where I designed a high-volume analytics and forecasting platform with MySQL-backed storage, prediction services, and API layers. I’d approach this similarly by separating raw feed ingestion, normalized event storage, market-structure computation, and serving interfaces. For this kind of system, I usually define replayable state transitions first, then evaluation logic around drift, regime changes, and signal stability. If ML is involved, I’d keep feature generation auditable and decoupled from inference. These systems need to be built for long-term production use, not just backtests that look good once. If useful, I can sketch the engine boundaries and data flow for ingestion, state computation, and signal delivery. Clifton

@nintysix96

Treat the bid amount and timeline as rough ballpark figures for now , we'll firm them up after a short chat about scope. You're building a proprietary market structure research platform, not a typical trading bot. The core of it is ingesting live Time & Sales from IBKR and splitting that data into two completely independent non-print engines: one tracking bid-side liquidity absence, the other ask-side. On top of that sits a custom LineBreak reconstruction engine and hooks for future AI and LLM-driven analysis. The goal is a clean, event-driven system you can actually do quantitative research on, not just backtest signals. Here's how we'd approach it: - IBKR data ingestion: Connect to the TWS/Gateway API with ib_insync, stream live tick data via WebSocket, and feed it into an async event bus so the two engines stay fully decoupled from the start. - Bid and Ask non-print engines: Each engine runs independently, tracking zero-print levels, liquidity voids, structural gaps, and persistence metrics as separate event streams stored in TimescaleDB with proper hypertable partitioning for fast time-range queries. - LineBreak reconstruction: Build the custom LineBreak chart engine from raw tick data rather than OHLC, so the brick construction logic reflects actual non-print structure rather than resampled candles. - Historical replay system: Store raw tick events in Postgres so you can replay any session through the engines later, which is essential for backtesting the AI layers cleanly. - AI/LLM integration hooks: Design the output schema from day one with feature extraction in mind, so plugging in a machine learning pipeline or an LLM analysis layer later is a matter of adding a consumer, not rearchitecting the core. After a short scope call we'll put together a written proposal covering deliverables, timeline and a firm price. Want to jump on a quick call this week to walk through the architecture before we quote firm numbers? Best, 96 Studio

@artur111shi

The engine will be built using Python and event-driven architecture. I will implement the necessary algorithms for market data processing and chart construction. The project is expected to be completed in 2 days. How will the AI integration be specified?