I build , deploy, optimize, and keep algorithmic trading systems running reliably in production — not just code, but execution that doesn’t break under real market conditions. 🧠 15 months hands-on across crypto, forex, and equities From strategy logic → to live execution → to infrastructure stability. ⚙️ What I actually do 🖥️ Infrastructure & Deployment Deploy trading systems on Linux (SSH, services, process control) Ensure uptime, auto-restarts, and crash recovery Handle real-world production issues (not theory) 📡 Execution & Connectivity Configure and maintain FIX connections Work with WebSockets + exchange APIs Migrate trading engines across exchanges & architectures 🔍 Monitoring & Debugging Deep log analysis & anomaly detection Fix execution mismatches, dropped fills, latency issues Debug binary market data streams 📊 Strategy & Data Build + backtest strategies (MQL5, PineScript) Data analysis with Python (Pandas, Matplotlib) Extract real signals from noisy datasets 🛠️ Tech Stack Linux · Python · C# · FIX Protocol · MQL5 · PineScript · Node.js WebSockets · CCXT · Docker · Pandas · Matplotlib 🎯 Who I work best with Traders who need systems that don’t fail live Quant devs who need execution + infra handled properly Teams tired of “it works locally but not in production” 📈 Track Record 400+ hours on a single long-term infra engagement 100% Job Success Score 🏆 Top Rated on Upwork If your trading system needs to run clean, stable, and production-ready — I handle that.

You have a trading strategy. Maybe it's live, maybe it's just a backtest, maybe it's a TradingView script you don't fully trust yet. The hard part was never the idea, it's making it run reliably when real money is on the line. That's what I do. I take trading strategies from concept → backtest → production execution, and I build the infrastructure that keeps them running. I don't sell alpha, signals, or "guaranteed returns." I'm the engineer who makes sure your system actually executes, accurately, every time, under live market conditions. What I build - Backtesting & research platforms with realistic fills, slippage, and fees, so your results survive contact with live markets - Live execution engines, async, fault-tolerant, built to recover instead of crash - Exchange & broker integrations over REST, WebSocket, and FIX - Real-time market data pipelines and order management systems - Monitoring, dashboards, and the production infrastructure that keeps it all alive Recent work - Built a NautilusTrader-based backtesting platform with a live performance dashboard - Audited and validated a multi-market algo system across NQ futures, forex, and commodities I hold a 100% Job Success Score with consistent 5-star reviews, and most projects turn into long-term work. Platforms & connectivity - Custom Python systems, NautilusTrader, QuantConnect/Lean, MetaTrader 5 (MQL5), NinjaTrader, and TradingView/PineScript, including converting TradingView scripts into real Python execution systems. - Exchanges: Binance, Bybit, OKX, Coinbase, Bitget. Brokers: Interactive Brokers, Zerodha, Dhan, Upstox. - Prediction markets: Polymarket, Kalshi. Whatever your edge, market making, arbitrage (CEX/DEX/cross-exchange), mean reversion, stat arb, options, or ML-driven, I've built and validated it in production. I implement and harden strategies; I don't claim to invent them. Background Before freelancing, I spent 8+ years building trading systems professionally, including a live market-making system trading BTC and ETH across Binance and OKX with ~12ms execution and Deribit options hedging, plus cross-exchange smart order routing for institutional OTC flow. I bring that same production rigor to every project here, whether it's your first bot or a fund's execution stack. If you want to automate a strategy, fix a backtest you don't trust, connect to an exchange or broker, or take an existing system into production, that's exactly what I do. Tell me what you're building.

I help hedge funds, proprietary trading desks, and advanced fintech teams design and build institutional-grade trading and research systems. My focus is not on toy backtests, but on execution-ready, decision-aware infrastructure that operates under real market conditions. I am a senior quantitative developer, algorithmic researcher, and strategy engineer with experience spanning high-frequency trading, systematic alpha research, execution systems, and institutional investment workflows. My work covers the full lifecycle of trading and investment systems, from market microstructure and low-latency execution, to top-down research frameworks that connect macro regimes, sector dynamics, security selection, and portfolio construction. Beyond implementation, I specialize in formalizing how investment teams think. I translate discretionary research and intuition into structured, explainable, and reproducible decision systems suitable for portfolio managers, investment committees, and client reporting. What I Do in Practice ✔️ Design and build execution-ready trading systems including HFT, statistical arbitrage, and market making ✔️ Architect institutional research frameworks linking macro, sector, security, and portfolio layers ✔️ Build strategy-aware infrastructure that enforces risk, explainability, and confidence calibration ✔️ Integrate machine learning and language models as decision support, not black-box signal generators ✔️ Deliver systems intended for live trading, capital deployment, and institutional scrutiny 💡 Core Expertise A. Trading and Execution Systems ✔️ High-Frequency Trading: microstructure modeling, latency optimization, execution efficiency ✔️ Statistical Arbitrage and Market Making: spread modeling, liquidity provisioning ✔️ Smart Order Routing and Trading Aggregators: multi-venue execution, real-time risk and connectivity B. Institutional Research and Decision Architecture ✔️ Top-down investment framework design across macro, sector, security, and portfolio layers ✔️ Research orchestration, dependency tracking, and explainable decision workflows ✔️ Converting discretionary research into auditable, reusable systems used by portfolio managers C. Quantitative Methods and AI ✔️ AI-augmented research systems using language models for structuring, synthesis, and scenario analysis ✔️ Machine learning for predictive modeling, anomaly detection, and regime analysis ✔️ Robust validation including walk-forward testing, stress testing, and stability analysis D. Crypto and Digital Asset Trading ✔️ CEX and DEX arbitrage, perpetuals, options, and AMMs ✔️ DeFi integrations and smart-contract-aware strategies 💻 Platforms & Infrastructure : Traditional Trading: MetaTrader 4/5 (MQL4/MQL5), NinjaTrader, Sierra Chart, TradingView (Pine Script), QuantConnect, Interactive Brokers, ThinkOrSwim Crypto Trading: Binance, Bybit, BitMEX, OKX, Deribit, dYdX, Uniswap, Sushiswap, GMX Low-Latency & HFT Development: C++, C#, Rust, Python, FPGA-based strategies Infrastructure & Pipelines: Kafka, Redis, TimescaleDB, PostgreSQL, Liquibase, Docker, Kubernetes AI & ML Toolkits: TensorFlow, PyTorch, Scikit-learn, OpenAI API, Pandas 💡 My Approach to Machine Learning and AI in Trading Financial markets are non-stationary, adversarial, and regime-driven. Machine learning and AI can add value, but only when applied with discipline and market awareness. I emphasize: - Alpha and economic logic first, machine learning second - Robust validation through walk-forward analysis and stress testing - Execution-aware design rather than theoretical backtests - AI as a tool for structuring reasoning and research, not for mining noise The same discipline applies to research systems. Strong investment outcomes come from clear assumptions, controlled uncertainty, and explainable logic rather than opaque models. 💬 My Philosophy on Pricing & Partnerships Exceptional value lies not just in technical ability, but in deep market understanding and execution precision. I focus on delivering results-driven systems, not just theoretical models. I welcome long-term collaborations with hedge funds, prop desks, and fintech startups who value strategic edge, not just code.

I build production-ready AI agents that bridge the gap between "cool prototypes" and actual business ROI. As a Computer Science student at UCF with a background in high-stakes algorithmic logic, I don’t just write prompts—I build scalable, autonomous systems. I specialize in multi-agent workflows and intelligent data processors that save businesses 10–40+ hours per week by automating complex manual tasks. What I Deliver: * Custom Multi-Agent Workflows: Designing "swarms" that handle lead qualification, CRM automation, and document parsing using LangChain and CrewAI. * MCP-Powered Integration: Implementing the Model Context Protocol (MCP) to give your agents secure, reliable access to your local files, APIs, and databases. * Data Intelligence: Advanced web scraping, structured extraction from PDFs/CSVs, and predictive modeling for actionable insights. * Financial & Quantitative Logic: Expert in algorithmic trading bots and strategy optimization (Pine Script, MT4/5, Genetic Algorithms) for high-performance financial workflows. Why Work With Me? * Engineering Mindset: A strong CS foundation means I focus on error handling, security, and performance—not just "chatting" with an LLM. * Outcome-First Approach: I provide clear milestones and fixed-price scoping so you know exactly when your system goes live. Let’s discuss your workflow pain points. I’m happy to audit your current process and propose a scoped solution that actually moves the needle.

I'm a Top Rated quantitative developer on Upwork, currently completing my MS in Data Science at Harvard, with production experience building and shipping algorithmic trading systems across futures, options, and equities. My work spans the full pipeline: from signal research and rigorous backtesting through execution architecture and live broker deployment. Over the years I've collaborated with professional traders, systematic fund managers, and independent CTAs on strategy research, execution system builds, and quantitative infrastructure — working with live accounts and real capital, not toy portfolios. - Research Philosophy Most algorithmic trading research fails before it reaches live markets. The reasons are almost always the same: data snooping bias, fragile parameterization, fill simulation that doesn't reflect actual execution, and strategy logic never stress-tested against regime change. My research process is designed to make it hard to fool yourself. That means strict chronological train/test splits with no parameter bleedthrough, walk-forward optimization over anchored and rolling windows, block bootstrap for inference on autocorrelated returns, and parameter sweep frameworks built to expose fragility rather than maximize backtest metrics. A strategy that only works on one parameterization isn't a strategy, it's a coincidence. I care about robustness across parameter space, regime stability, and understanding exactly why a signal works before scaling it. I work extensively in QuantConnect's LEAN engine for research-grade backtesting and live account deployment, though deployment targets vary by strategy and client stack. IB TWS via ibapi, Tradovate, and NinjaTrader are all in regular rotation depending on execution requirements. I build custom analytics layers on top of backtest output: Sharpe decomposition, drawdown attribution, execution cost modeling, and signal decay analysis, because standard tearsheet metrics rarely tell the full story. - Strategy Coverage My research spans futures (NQ, ES), SPX and index options, ETFs, and crypto. Strategy types I've built and validated in production include intraday momentum and trend-following systems, mean reversion and stat-arb frameworks, breakout and scalp architectures with dynamic sizing tiers, options strategies including iron condors, defined-risk vertical spreads, 45-DTE and 0DTE SPX structures with delta-based hedge logic, and GEX (gamma exposure) driven directional frameworks using open-interest-weighted dealer positioning data. It's an area where the signal literature is still thin and where getting the methodology right matters more than most people acknowledge. - Execution Engineering The research-to-live gap is where most systems break. I build execution infrastructure that closes that gap: Interactive Brokers TWS via ibapi with state machine architectures, order ladder geometry, true breakeven calculations with commission and slippage factored in, and hedge math for multi-leg positions. On the NQ/ES side I've built and audited scalp bot execution logic on Tradovate, integrated Databento for professional tick data pipelines with proper validation against reference data, and developed Pine Script strategies and indicators on TradingView for signal prototyping before committing to full implementation. I'm also familiar with NinjaTrader's execution environment and ATM framework. Code I deliver is production-standard: structured logging, explicit edge-case handling, clean separation of signal and execution layers, and documented at a level where the system is maintainable after handoff. - What I Work On: - Strategy Research & Backtesting: QuantConnect/LEAN, Backtrader, Zipline, VectorBT, QuantLib, Python - Execution Systems: IB TWS/ibapi, Tradovate API, NinjaTrader, REST/WebSocket broker integrations, FIX Protocol - Retail Platform Development: MQL4/MQL5 (MetaTrader 4/5), Pine Script (TradingView), NinjaScript (NinjaTrader 8), EasyLanguage (TradeStation), ThinkScript (Thinkorswim), cAlgo/C# (cTrader), AFL (AmiBroker) - Broker APIs: Interactive Brokers, Alpaca, TD Ameritrade, Tradovate, Oanda, Databento - Crypto Platforms & APIs: Binance, Bybit, OKX, Kraken, Coinbase Advanced Trade, Bitfinex, Deribit (options/derivatives), KuCoin, Gate io, Freqtrade, Hummingbot, 3Commas, Pionex, Gunbot, ccxt (unified exchange library) - Statistical Testing: Walk-forward testing, parameter sweep analysis, Monte Carlo simulation, bootstrap inference - Full-Stack Delivery: Data ingestion → signal research → backtesting → live deployment

I help startups and teams build and scale AI-powered products on Replit — from quick MVPs to fully deployed SaaS systems. Whether you need agentic workflows, Replit deployments, or cross-platform apps, I turn complex ideas into working, production-ready solutions. With 8+ years of full-stack experience, I’ve delivered projects across AI, Replit, TradingView integrations, and React Native, helping clients launch faster and scale confidently. Core Expertise: 🔹 Replit Development & Deployment – end-to-end app builds, Replit-hosted SaaS, debugging, migrations 🔹 AI & Agentic Systems – OpenAI, Claude, MCP, Cursor, custom AI workflows 🔹 Full-Stack Engineering – Node.js, Firebase, REST APIs, Electron 🔹 Mobile Development – React Native, Expo, hybrid mobile apps 🔹 Trading Tools – TradingView, Pine Script, custom charting libraries Clients describe me as proactive, reliable, and solution-driven — not just fixing problems but building scalable, maintainable products that last. If you’re looking for a Replit expert who can design, code, and deploy your next AI or full-stack project, let’s connect and make it happen.

I am a Forex Trading Programmer with over 5 years experience. 👍My primary expertise lies in MQL4, MQL5, PineScript, Python and C#.👍 👍Nowdays, I connected the tradingview and another system with Python.👍 I am also well-versed iin using trading platforms such as MetaTrader, TradingView and NinjaTrader. Throughout my career, I have developed a variety of strategies and indicators tailored to meet my client's specific needs. My work includes implementing populer strategies like Grid and Martingale. 👍My another skill is AI trading bot development.👍 👍Also, I have developed the MetaTrader license system.👍 👍One of my standout projects was the development of a Copy Trading Sytem for MetaTrader and Tradelocker.👍 👍Pinescript is my skill.👍 I take pride in my ability to create innovative solutions in the trading domain. And also, I developed and integrated the API as like slack, tg for automation trading. My strong technical skills, combined with a deep understanding of trading concepts, allow me to deliver high-quality programming services. I am committed to helping clients achieve their trading goals through effective and efficient software solutions. Let's get started. Best Regards

Senior Algo Trading Developer | cTrader (c#), TradingView & NinjaTrader You need a developer who understands market structure, not just syntax. As a software engineer and active trader with nearly 10 years of experience, I build professional trading systems that do exactly what you expect them to do—reliably and precisely. I have completed 100+ trading projects, delivering maintainable, clean code rather than "quick hacks." My core expertise includes: cTrader / cAlgo (C#) Custom cBots, indicators, and trade management systems. Licensing systems and dashboards. Note: I am an active contributor to the cTrader Developer Network (CTDN), ensuring strict adherence to platform architecture. TradingView (Pine Script v4/v5) Strategy and indicator development. Multi-timeframe logic, scanners, and alerts. Converting ideas into non-repainting scripts. NinjaTrader 8 (NinjaScript) Advanced automated strategies and execution logic. Custom UI tools for discretionary or systematic trading. Why work with me? I don’t just "code what you say." I challenge unclear logic and help you refine your edge to ensure the final system behaves correctly under real market conditions. I understand risk management, execution rules, and edge preservation. If you value precision, honesty, and experience, let’s discuss your strategy.

Looking to build stable, production-ready AI applications backed by high-performance architecture? I am a Senior .NET Developer and AI Engineer with over a decade of hands-on experience designing robust backend architectures for high-transaction industries like Banking and Crypto Exchanges. I specialize in building the secure infrastructure required to run reliable AI applications—focusing on advanced Retrieval-Augmented Generation (RAG) pipelines, LLM integration, and multi-agent systems. By leveraging C# .NET Core and Docker-distributed environments, I ensure your AI initiatives move seamlessly past the prototyping phase and scale safely in production. 🛠️ CORE AI & BACKEND CAPABILITIES: • AI Orchestration & RAG: Architecting advanced Retrieval-Augmented Generation (RAG) pipelines, semantic data strategies, and multi-agent systems using modern LLM frameworks. • Enterprise .NET Architecture: Designing secure, high-throughput C# .NET Core microservices, WebAPIs, and robust transaction layers. • Database & Query Optimization: Advanced T-SQL data modeling and performance tuning to handle complex underlying datasets efficiently. • Containerization & Deployment: Building and isolating AI workloads across robust Docker-distributed infrastructure environments. 💼 INDUSTRY-GRADE RELIABILITY: • FinTech & Banking Foundations: A proven track record of engineering multi-tenant banking products and crypto-fiat exchange platforms under strict delivery standards. • Production-First Mindset: Your proprietary business data remains secure, token usage stays optimized, and your AI systems are built to scale rather than break. Let’s move your AI project beyond a simple template and into a resilient production system. Click "Invite to Job" to discuss your project!

Tradestation/Multicharts Programming. Convert Pine Script (from Trading View) indicator/strategy into TradeStation EasyLanguage. Convert NinjaTrader indicator/strategy into TradeStation EasyLanguage. Convert AmiBroker indicator/strategy into MultiCharts PowerLanguage. I am also proficient in developing indicators and strategies on TradingView. I have more than 20 years of experience in the IT industry, and I am also a database expert. I’ve programmed hundreds of indicators and strategies. Let's discuss how we can turn your ideas into automated strategies or indicators.