Python Dev for Quant Trading Engine

@ska234

Hi. To build this, I’d set up an event-driven Python pipeline around IBKR Time & Sales, with async ingestion, a clean event bus, and persistence into PostgreSQL/TimescaleDB for replay and research. The non-print bid/ask engines would be separated at the data layer, then fed into 200 lightweight in-memory Line Break state machines so CPU and memory stay controlled. I’d expose the structural states through JSON and WebSocket APIs, and keep the dashboard focused on one main trading view plus compact status panels for each engine. As a Senior Backend Engineer, I have mastered Python, Interactive Brokers API, event-driven market data systems, and custom chart/data-structure construction, and have strong experience in quantitative trading platforms, tick-data storage, and replay engines. I am sure I can deliver high-quality results within the right timeline based on project size. Let’s get in touch and discuss more. Thanks.

@PINESCRIPTERR

Hello, I can help with "Python Dev for Quant Trading Engine" and keep the work clean and practical. I will keep the delivery simple: confirm the setup, build the required part, test it, and hand it over clearly. I also noticed the listed skills include Python Data Processing Algorithm Software Architecture Financial Markets Machine Learning (ML) MySQL Data Mining Artificial Intelligence API Integration. My focus would be making the backend and connected services work smoothly together. To set this up properly: 1. Should the solution be optimized for future scaling, easier maintenance, or a simple handover? 2. What integrations should be connected first, and do you have API docs or test access ready? 3. Can you share a sample input and the exact output format needed for the data flow? Regards, Houssame

@krupnovdenis

Hello! We can build you a custom market data platform for this task. 1. Are you open to working with an external contractor or team for these tasks? 2. Which parts should be covered first: data ingestion, line break engines, 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!

@mahads31

As an experienced freelance Python developer with a deep understanding of the intricacies of financial markets, I believe I can bring immense value to your custom market structure research and analysis platform project. My skill set includes proficiency with the Interactive Brokers API, real-time market data processing, time & sales analytics, multithreading, asynchronous programming, and trading system development among others – all of which have direct relevance to your project's needs. Furthermore, I am well-versed in working with market microstructure concepts, order flow analysis, liquidity modeling, AI integration, LLM integration, and machine learning pipelines - skills that would be particularly valuable given your interest in leveraging AI-driven analysis and strategy development in the future. Finally, my experience with databases like PostgreSQL/TimescaleDB will be instrumental in designing a robust system to store and manage the extensive datasets you anticipate generating. With me on your team, not only will you have a programmer capable of accurately constructing proprietary Line Break charts from non-print datasets, but also a technology partner who is invested in the long-term success and scalability of your unique tool. Let's build something incredible together!

@durgesh8527

As an experienced full-stack development team, my associates and I would be an excellent choice for your project. With over a decade in the industry, we've gathered significant acumen working on large-scale, data-centric applications, which perfectly aligns with your needs for this Python-based Quantitative Trading project. Our deep understanding of event-driven architecture and market data processing, including proficiencies with Interactive Brokers API (IBKR), PostgreSQL and TimescaleDB, enable us to implement robust systems catering to your specific requirements. Additionally, we possess substantial knowledge in WebSocket architecture along with multithreading and asynchronous programming skills that would prove invaluable to you given the real-time nature of the data you are working with. We're also well-versed in developing both trading systems as well as quantitative research tools. Over the years, we've developed an instinctive understanding of market structures as well as order flow analysis that will surely enhance our effectiveness on your project.

@ayesha86664

Hi there! When a construction website has display issues and weak Google visibility, it directly reduces trust and leads because users assume the business is inactive or unprofessional. Even small technical issues like font errors or broken email delivery can cause lost inquiries without you noticing. I am a web developer and SEO specialist with experience in fixing live websites, improving performance, and optimizing them for search engines. I have worked on WordPress and custom CMS sites where I handled technical SEO, on-page optimization, speed improvements, and lead generation setup. I also have experience fixing email delivery issues, UI inconsistencies, and improving overall site reliability. My approach will start with fixing your current website issues including font rendering and email delivery problems. Then I will optimize your website speed, structure, and mobile responsiveness for better user experience. After that, I will implement on-page SEO for your key services like roofing, siding, and remodeling to improve Google rankings. Finally, I will ensure proper indexing setup and tracking so you can monitor leads and traffic clearly. check our work https://www.freelancer.com/u/ayesha86664 Which platform is your website built on (WordPress, custom PHP, or another CMS)? Let me know if you’re interested & we can discuss it. Best Regards Ayesha

@mojjammil

Hello, I am ready to start immediately and believe my background aligns well with the architecture you’re building. I have extensive experience developing Python-based data processing systems, event-driven backends, and quantitative research tools with a focus on performance, scalability, and maintainability. My work includes real-time market data ingestion, asynchronous processing pipelines, custom analytics engines, PostgreSQL-backed applications, and AI-ready data architectures. For your platform, I would structure the solution into modular components: * Real-time IBKR Time & Sales ingestion service * Independent Bid and Ask Non-Print processing engines * 200 internal Line Break state engines maintained as lightweight data structures * Classification layer driven by your supplied formulas * PostgreSQL/TimescaleDB persistence for raw and derived data * Replay engine for historical analysis * Dashboard exposing a single rendered chart plus lightweight structural status panels * AI-ready interfaces via JSON and API/WebSocket endpoints I would be glad to discuss the architecture and implementation details in more depth. Kind regards, Mojjammil

@smitk9999

Hello, I can help with the Python, IBKR API, PostgreSQL/TimescaleDB, WebSocket, async architecture for your non-print market structure platform. This scope is far beyond a $20 full build, but I can use the initial budget for a focused technical discovery: review your classification rules, define the Bid/Ask non-print engine structure, outline the 200 internal LineBreak engines, and prepare a database/API/replay architecture plan. I have experience with Python backend systems, real-time APIs, event-driven processing, database design, WebSocket pipelines, and AI/LLM-ready data workflows. I’ll keep the LineBreak charts as internal data structures, not visual charts, to minimize CPU and memory usage. After discovery, I can break the full platform into fixed milestones: IBKR ingestion, engines, classifications, storage, dashboard, replay, and AI-ready endpoints. I am ready to start. Best regards, Smit

@goranm16

Hi, this is a good fit for my work because the real goal is a real-time data processing engine, not a simple trading bot. I would approach it by first building a small proof-of-concept around IBKR Time & Sales ingestion, then separating bid/ask non-print events into clean internal data structures before adding the LineBreak reconstruction and storage layer. The main risk is performance and state accuracy across 200 internal engines, so I’d keep the design event-driven, test each engine with replay data, and expose clean JSON/WebSocket/API outputs for later AI or LLM analysis. I can also help design the PostgreSQL/TimescaleDB schema and a lightweight dashboard with one main chart plus status panels. For the $20 max, I’d suggest starting with a compact architecture + working prototype scope rather than the full platform. Thanks!

@cuyodigital

I looked at your quant trading engine and need to build IBKR Time & Sales into separate Bid/Ask non-print engines with 200 internal Line Break data structures and a dashboard with one rendered chart. You can see my market data work at https://www.freelancer.com/u/cuyodigital. Deliverables include both non-print engines, 200 Line Break data structures, classification framework integration, dashboard with status blocks, historical replay, and documentation. The project will be completed in 5 days at 20 USD. For the Line Break construction, do you define thresholds as price-based or volume-based? For status blocks, do you want color codes or numerical scores first? Let me know your answers. I can start right away.

@hoangvanp

Hi, I can develop a custom Python-based market structure research and analysis platform utilizing Interactive Brokers Time & Sales data to build separate Bid and Ask non-print data engines, each with unique structural datasets for liquidity modeling and absence analysis. The system will also include 200 Line Break data engines internally stored as data structures, not visual charts, accurately constructed to support downstream classification logic. I have experience with Python, Interactive Brokers API, real-time market data processing, and custom chart construction. For this project, I would begin by implementing the Bid and Ask non-print data engines, constructing Line Break charts, integrating the classification engine, and designing a dashboard with a primary trading window and structural status panels. A key challenge is ensuring efficient performance to minimize CPU and memory usage while supporting real-time updates, historical replay, and future AI integration. I will provide fully documented Python code, database schema, real-time data ingestion, Line Break engines, classification framework, dashboard UI, and historical replay capability. Let's discuss the details via chat. Regards,

@Lazarone1

Hi, I can build this market-structure research system in Python with IBKR real-time data, event-driven architecture, and a clean separation between Bid/Ask non-print engines. I’ve worked on tick-data pipelines, async trading systems, and TimescaleDB/PostgreSQL storage layers for high-frequency data. I would design a modular engine where Time & Sales feeds into independent structural processors, with LineBreak state machines stored as in-memory + database hybrid for performance. Everything would be API/WebSocket ready for future AI integration, with a lightweight dashboard showing the 200 structural states as requested. Happy to break down architecture, timeline, and cost once we align on exact IBKR data format and classification rules.

@Ritesh11gupta

I see you're looking for a Python developer for a quant trading engine. I have solid experience with API integration and data processing. What specific strategies or models are you considering for this project?

@shameelarif

Hello there, I hope you are doing well. I understand you are looking for an experienced Python developer to build a high-performance market structure research platform using Interactive Brokers Time & Sales data, focused on Bid/Ask non-print engines, custom Line Break data structures, and future AI integration. I can help you design and build a scalable, event-driven system that handles real-time data processing, structured storage, and analytical engines optimized for continuous operation. For your project, I will: -Build a real-time data ingestion system using Interactive Brokers API -Implement event-driven architecture for Time & Sales processing -Develop separate Bid and Ask Non-Print data engines -Create 200 internal Line Break data structures (100 Bid / 100 Ask) without visual rendering overhead -Design efficient in-memory + PostgreSQL/TimescaleDB storage system -Implement classification framework integration (compression, expansion, dominance, etc.) -Build a lightweight dashboard with 1 main chart + 200 structural status panels -Ensure real-time updates with WebSocket/API support -Optimize system for low CPU and memory usage for continuous operation -Structure backend for future AI/ML integration and data consumption -Deliver fully documented, production-ready Python code with setup instructions 2 Looking forward to hearing from you soon! Best regards, Shameel

@josep438

Hi there, I can build your proprietary market structure research engine to process Interactive Brokers Time and Sales ticks into your non-print liquidity models. I design low-overhead systems using asynchronous Python and memory-optimized data structures, keeping your 200 internal Line Break arrays purely in-memory rather than wasting CPU on graphic renders. For the storage backend, I heavily utilize TimescaleDB hyper-tables to compress tick events and structural classification states efficiently. You can evaluate my background in financial engineering, raw data capture, and reverse engineering through my work on financial engineering and MQL5 algorithm updates for MetaTrader Expert Advisors as well as my experience in advanced Python optimization, packet sniffing, and multithreaded automation script development. I have built event-driven IBKR trading systems, and for a production-grade infrastructure, I estimate a timeline of three to four weeks at a milestone budget we can finalize together based on your data throughput needs. Let us open a chat to discuss your classification state formulas and the WebSocket JSON schemas for future AI agents. Best regards, Jose

@snath88

Hi, Drop me a message — I'll share a quick prototype based on what I understood. If it matches your expectations, we can move forward. Thanks!

@nutankumarftp

With your project's focus on building a proprietary market structure research and analysis platform, my decade-long experience in full-stack development with expertise in Python, Database (particularly PostgreSQL), and WebSocket architecture checks off your major requirements. My understanding of working with APIs, including Interactive Brokers' API(IBKR), and fluency in Python for real-time market data processing make me an excellent fit for architecting your time & sales data-driven system. Additionally, I see your preference for TimescaleDB matches my proficiency alongside my constructive mastery of front-end technologies like React.js, which could effectively contribute to a single primary dashboard with lightweight structural status panels as requested. Furthermore, I have experience working on complex projects that demand intelligent problem-solving skills and meticulous data management-qualities crucial to the success of your AI-driven quantitative trading engine. My extensive work on trading systems would resonate positively with this project as it delves into essential aspects such as liquidity modeling, order flow analysis, and AI integration. I'm well accustomed, from deep space optimization to structuring Big NON-PRINT datasets overlients- to managing large volumes of data in a way that is efficient, scalable, and future-ready.

@jamik414

Hello, I am an experienced Python developer with expertise in market data processing and algorithmic trading systems. For your custom non-print market structure engine project, I will utilize my skills in Python, Interactive Brokers API, real-time market data processing, PostgreSQL, WebSocket architecture, and custom chart construction. I will focus on building a robust system for future AI-driven analysis and strategy development. My approach involves developing separate Bid and Ask non-print data engines to model liquidity absence accurately. Additionally, I will construct Line Break charts as critical data structures and implement a classification engine based on provided formulas. The system will efficiently store data in PostgreSQL or TimescaleDB and provide a user-friendly dashboard for easy monitoring. Smooth communication during United States time is assured throughout the project. Best regards, Jamila

@sanddep5

As an experienced and versatile Full Stack Developer, I possess the unique skill set necessary for this complex project. My expertise in Python and strong understanding of market data processing and algorithmic trading systems are an ideal fit for your Quantitative Trading Engine. Since your project is centered around market microstructure, order flow analysis, and liquidity modeling, my previous work in these areas will allow me to accelerate your platform development. Moreover, my proficiency with the Interactive Brokers API and real-time market data processing frameworks reinforce my ability to handle the challenges of this assignment. I have also worked with PostgreSQL and TimescaleDB, aligning closely with your preferences for data storage solutions. Additionally, my knowledge of WebSocket architecture, multithreading, asynchronous programming facilitate the construction of a robust and high-performance system that can efficiently process historical replay data. Lastly, as someone well-acquainted with AI and machine learning pipelines, I genuinely appreciate your vision for future AI-driven analysis and strategy development within your trading platform. My experience extends beyond just building algorithms; I strive to understand how technology can enhance business outcomes.