I am a quantitative / systematic trader that also helps others with all things related to running algorithmic trading systems. With 8 years of dedicated experience in financial markets, including extensive trading in the Futures and Options (F&O) segment of Indian markets, I offer a comprehensive understanding of trading dynamics and strategies. My expertise extends to developing Real-Time Trading Applications, Back Testing/Modeling Trading Strategies, data collection/storing, portfolio and position risk management, etc. using Python and TradingView as my primary tools. I am a skilled python programmer that writes well documented and organized code that is easy to follow and build upon. I provide even more value with my trading knowledge and experience. I've developed more than 60 successful projects to date helping Retail and Institutional Clients, and look forward to taking on many more. No matter how large or small the project, I am capable of completing it in a timely and effective manner. THINGS I CAN HELP YOU WITH : 🌟 Algo Trading Bot / Application - Coding your strategy and integrating it with brokers api in python. Fast, Accurate, Efficient, Documented code deployed on cloud or locally. 🌟 TradingView + Python - Trading Logic and Signals are coded in TradingView Pine Script and trade execution is done through Python and Brokers API. 🌟 Equity Markets - Indian Markets, US Markets, major Global Markets using broker APIs. Direct Equity, Futures and Options, Delta Trading. Experience with Interactive Brokers, TD Ameritrade, E-Trade, Zerodha, Kotak, Upstox, IIFL, Angel and others. If it supports algo trading, I've either developed on or can very quickly learn how to. 🌟 Crypto Markets - Binance, Kucoin and all major Crypto Exchanges. Grid Trading, Arbitarage Trading, Option or Futures. 🌟 TradingView PineScript - Custom Indicator Development, Modification or bug fixing in existing Indicator or strategy, Generate and Send Alerts to Trading Bot or Messaging Channel. 🌟 BackTesting - Develop Custom Backtesting modules based on your needs, or using open source libs like VecorBT, BackTrader, BackTesting, etc. in python further optimised with . Fine Tune or optimise parameters based on market conditions. 🌟 Risk Management - Integrated Position Sizing, Portfolio Risk Analysis, daily limits for trades, profits or loss. 🌟 Data Analysis & Visualization - Analyse data with Pandas, Numpy, Numba, Scipy and view it in excel or webapp. Charting Libraries such as Seaborn, Tableau or MatPlotLib and seamless integration with MySQL, PostGreSQL or others. 🌟 Signal and Trade Messages - Get Custom Messages on Signal / Order / Trade on Telegram, Discord, WhatsApp, E-Mail, etc. 🌟 User Interface - Request Custom Website in React js with FastAPI or Dash Webapp, Simple Excel / G Sheet, GUI App build with PyQT. 💼 Work Approach: Shoot me a message and lets chat over zoom via the Upwork integration and quickly discuss your project needs. The consultations are free, and last as long as needed. It can be 2 minutes or 2 hours. My goal during this call is to ask you as many questions as I need until my brain clicks and fully understands your project. 🤝 Let's Collaborate: If you're seeking a skilled professional to enhance your trading operations or develop custom solutions, I'm here to help. Let's discuss your requirements in detail and explore how we can collaborate to achieve success in the dynamic world of financial markets. Feel free to reach out, and let's embark on this journey together. Kind regards 😊 Have a good day and stay safe, Harsh Kantariya.

Quant Scientist with over 5 years of experience in financial modeling, algorithmic trading, and machine learning. I specialize in building and deploying data-driven systems for forecasting, strategy development, and risk management — with deep expertise in time-series modeling and Python-based tooling. Currently, I work at a Global Macro Hedge Fund where I design and implement systematic strategies across asset classes, build portfolio optimization tools, and develop quantitative risk frameworks. Outside of work, I actively research and trade in equities and digital assets, with hands-on experience developing DeFi strategies (arbitrage, trend-following, yield optimization) since 2021. What I Can Help You With? - Development and backtesting of trading strategies (equities, crypto, futures) - Predictive modeling & machine learning (scikit-learn, TensorFlow) - Time-series analysis and signal engineering - Custom data pipelines: APIs, scraping, structured storage - Interactive dashboards and analytics (Dash, Plotly) Tech Stack - Languages & Libraries: Python, NumPy, Pandas, Scikit-learn, XGBoost, TensorFlow, Statsmodels, Git - Backtesting & Strategy Simulation: Backtrader, VectorBT, QuantConnect (LEAN) - Risk & Portfolio Analysis: Pyfolio, Riskfolio-Lib, Empyrical, cvxpy, Quantlib - Forecasting: Scikit-learn, XGBoost, TensorFlow, Darts, TSFresh - Data & Automation: REST APIs, Web Scraping (Selenium, BeautifulSoup), SQL, ArcticDB - Visualization & Dashboards: Plotly, Dash, Seaborn - API Integration: Interactive Brokers API (ib_insync), CCXT (CEXs), Web3.py, The Graph (on-chain data), 0x API - Infrastructure & Workflow (Optional): Docker, Airflow, AWS (EC2, S3), Git - Options: understanding of theory, including Greeks, implied volatility, and surface construction

📌 About Me I am a PhD-level engineer specializing in mathematical modeling, and scientific algorithm development, with a strong skills for algorithmic trading and quantitative research. I help traders, fintech startups, and prop firms turn trading ideas into robust, validated, and fully automated strategies that perform reliably in real-market conditions. My work sits at the intersection of scientific rigor, quantitative finance, and professional software engineering. Clients come to me when they want trading systems that are mathematically sound, stress-tested, and coded with precision. ⸻ 📌 Why Clients Hire Me I combine the depth of academic research with the practical methodologies used by top quant professionals. My work draws inspiration from: Legendary quants: Jim Simons, Ed Thorp, Marcos López de Prado, Perry Kaufman Top algorithmic trading experts: Ernest Chan, Kevin Davey, Andrea Unger, Howard Bandy I do not build “black-box” systems — I build transparent, reproducible, and professionally validated strategies. ⸻ 📌 What I Can Build for You I develop strategies ranging from simple rule-based models to advanced machine-learning systems, including: ✔ Fully automated trading bots ✔ Indicator-based rule systems ✔ Statistical & time-series models ✔ Machine learning (ML) and pattern recognition ✔ Multi-asset and portfolio strategies ✔ High-integrity backtesting pipelines ✔ Walk-Forward Analysis & Monte Carlo Stress Tests Everything is developed with a strong emphasis on robustness, reproducibility, and avoiding curve-fitting. ⸻ 📌 Technical & Quantitative Skills Algorithm Development • Strategy design (trend, mean-reversion, breakout, volatility models) • Multi-timeframe & multi-asset logic • Entry/exit signal engineering • Portfolio allocation and position sizing Backtesting & Validation • Walk-Forward Analysis (WFA) • Monte Carlo simulations • Overfitting detection • Robustness testing • Data integrity & reproducibility control • Probabilistic validation of model outputs Quantitative Analysis • Time series modeling • Noise reduction and signal filtering • Risk/return evaluation (Sharpe, Sortino, DD…) • Statistical diagnostics and cross-validation ⸻ 📌 Programming & Technical Stack Python, Trading, Machine Learning & API Stack • NumPy, Pandas, SciPy, statsmodels, arch • TA-Lib, pandas-ta, btalib • Backtrader, Zipline, VectorBT, PyAlgoTrade, PyFolio • PyPortfolioOpt, QuantStats • scikit-learn, XGBoost, LightGBM, CatBoost, Optuna • TensorFlow, Keras, PyTorch, Prophet • ccxt, Alpaca API, IBKR API, Oanda, MetaTrader Python Bridge • yfinance, AlphaVantage, Polygon.io, Quandl • requests, aiohttp, BeautifulSoup, Selenium • SQLAlchemy, sqlite3, PostgreSQL (psycopg2) • Parquet, HDF5, Feather for large datasets • numba, Cython, multiprocessing, joblib • Matplotlib, Plotly, Bokeh, mplfinance • Git, GitHub, GitLab, CI/CD, Docker • pytest, flake8, black, pydantic, logging Trading Languages & Platforms • EasyLanguage (MultiCharts) • MT4/MT5 (EA development) • Java for high-performance algo logic • API integration: ccxt, yfinance • Web scraping (Requests, BeautifulSoup) • Git/GitHub version control & CI automation ⸻ 📌 Collaboration & Delivery I work with: • Independent traders • Prop firms • Fintech startups • Quant teams needing R&D support I can translate any trading idea — even vague or experimental ones — into a clean, documented, testable model. ⸻ 📌 What You Receive ✔ A fully working, tested trading strategy ✔ Complete and clean source code ✔ A detailed professional performance report ✔ Drawdown, Sharpe, win rate, robustness metrics ✔ Walk-Forward + Monte Carlo stress testing ✔ Support for improvements and refinements ⸻ 📌 My Work Philosophy I don’t deliver “pretty backtests” — I deliver strategies designed to survive real markets. If you want a rigorously tested, professionally validated, and production-ready trading system, I’d be happy to help.

I build production highly scalable systems, from Quantitative Research board which market data ingestion to live execution; for funds, prop desks, and serious retail traders. 9+ years in software engineering, the last several spent almost exclusively on trading infrastructure: IBKR/MT5/FIX execution, tick-level data pipelines, and causal ML for signal generation. I run my own live trading platform, so I'm not learning on your dime — I ship what I already operate. What I Build: ⤷ End-to-end Algo trading systems (data → signal → execution → risk) ⤷ Broker/exchange integrations: IBKR API, MT4/MT5 (MQL5 EAs), Binance, Bybit, Polymarket ⤷ Low-latency execution infrastructure (Dockerized IB Gateway, multi-instance live trading, C# ↔ MQL5 bridges) ⤷ Causal inference for markets: PCMCI+, VarLiNGAM, DYNOTEARS, Granger/Transfer Entropy — used to filter spurious signals before they hit a backtest. ⤷ ML signal models: LightGBM, XGBoost, LSTM/TCN, meta-labeling over causal-discovery gates ⤷ Backtesting & research stacks: NautilusTrader, Backtrader, Zipline, QuantConnect, Qlib. ⤷ Market microstructure work: LOB/MBP-10 data, Hawkes processes, Hayashi-Yoshida covariance, price discovery (Hasbrouck/Gonzalo-Granger) ⤷ Options pricing & Greeks (Black-76, BSM, second-order Greeks) for hedging and 0DTE workflows ⤷ Financial data engineering: Databento, TimescaleDB, Parquet/Arrow pipelines Core Stack: ✓ Backend: Python (FastAPI, Django), C#/.NET, Rust, C++ ✓ Data: TimescaleDB, PostgreSQL, Redis/Valkey, Parquet, Apache Arrow/PyArrow ✓ Cloud/Infra: AWS (ECS, Lambda, RDS), Docker, Terraform, Packer, GitHub Actions CI/CD ✓ Trading: IBKR API, MetaTrader 5/MQL5, TradingView, Databento (GLBX.MDP3/MBP-10) ✓ ML/Causal: PCMCI+, CMIknn, LightGBM, XGBoost, scikit-learn, statsmodels Why Clients Choose Me: ✓ I operate a live trading platform myself — I understand uptime, restart cycles, and the failure modes that only show up in production ✓ Rigorous methodology: I don't just backtest, I stress-test causal assumptions before trusting a signal ✓ Clean, documented handover, you're not locked into me ✓ Clear async communication with regular progress updates Recent Results: - Rebuilt an IBKR Gateway deployment to eliminate recurring 12-hour restart cycles caused by GDI handle leaks - Designed a causal-discovery pipeline (PCMCI+/CMIknn) identifying dominant cross-asset drivers in equity stress regimes - Architected a C# Worker Service + MQL5 EA bridge for automated MT5 execution - Live trading volume: $80M+ across managed strategies (2025) - Built AWS Savings Plan / Reserved Instance cost model cutting infra spend without sacrificing uptime SLAs Send me your requirements and I'll respond within 2-6 hours with a concrete plan.

I'm a Senior Aussie developer living in Europe with more than 19 years of hardcore software engineering experience. I began my career in Australia and now work remotely for mostly American corporations with strong cross over across US timezones. Highlights: - 18,000+ hours on upwork - 100% success rating top rated plus My skill set is as follows. 💎 Backend skills: ✔✔✔ PHP 7.x ✔✔✔NodeJS ✔✔✔Laravel Framework (5.x) ✔✔✔ NestJS ✔✔✔ Prisma ORM ✔✔✔ Graphql subscription, graphql-codegen, type-graphql ✔✔✔ CQRS ✔✔✔DDD ✔✔ AdonisJS ✔✔✔ Composer ✔✔✔Advanced architectural design patterns 🖼 Frontend: ✔✔✔React ✔✔✔VueJS ✔✔✔ RXJS ✔✔✔ GraphQL , GraphQL subscriptions, cache, link state ✔✔✔ Websockets/Real-time updates 📁 Databases ✔✔✔ Supabase with RLS/ multi-tenancy ✔✔✔ Mysql ✔✔✔Postgres ✔✔ DynamoDB ✔✔ Cassandra ✔✔ MongoDB 🗄Caching: ✔✔✔ Redis with clusters ✔✔memcache 📊 Streaming: ✔✔✔ Websockets ✔✔✔ Kafka ✔✔✔ socketio + Pusher + PubNub ✔✔✔ Redis Pub/Sub ⌛ Dev-ops: ✔✔✔ Kubernetes ✔✔✔ K8s Secrets / Namespaces ✔✔✔ Helm charts ✔✔✔ Linux/Apache/Nginx/Varnish Cache ✔✔✔ Jenkins / Bamboo CI / Buddy ✔✔✔ Docker and VirtualBox ✔✔✔ AWS / s3 / Route 53 / ECS / EC2 / ECR / EKS / GCP / Azure / Amplify ✔✔✔ AWS Serverless ✔✔✔ Testing: Cypress, PHPUnit, Jest, Mocha, Chai ✔✔✔ E2E/BDD/TDD Unit Testing / Protractor / Selenium ✔✔✔ Kubernetes Secrets management AI: ✔✔✔ Knowledge of OpenAI endpoints ✔✔✔ Api integration with eleven labs voice platform ✔✔✔ Langchain / AutoGPT / SQLAgent / Mastra ✔✔✔ Voice APIS - livekit/retell/vapi 🧱 API Development: ✔✔✔Twilio ✔✔✔ Docusign API ✔✔✔ Tesseract ✔✔✔PyTesseract ✔✔✔Backtrader ✔✔✔ OpenCV ✔✔✔ Pyfolio ✔✔✔ OpenGL ✔✔ Tensorflow ✔✔✔Stripe

🎯 I build trading systems that actually trade well, not just scripts that compile. I'm an active ICT/SMC trader (Gold & Crypto) who codes. I build Pine Script strategies, MQL5 EAs, and Python trading bots, with 19 completed projects and a 100% Job Success score. This rare combo means I understand WHY your strategy needs to work, not just HOW to code it. ✅ 100% Job Success ✅ 5.0 rating (15 reviews) ✅ 19 projects, 271 hours ✅ Active Gold (XAU) + Crypto trader ✅ Fast turnaround ✅ English fluent 🔧 Trading & Algo Development: ✅ Pine Script (v5/v6): custom indicators, alerts, multi-timeframe ✅ TradingView strategies: full backtest with detailed reporting ✅ ICT/SMC concepts: FVG, Order Blocks, BOS, CHoCH, liquidity ✅ MT5 / MQL5 EAs: entry logic, ATR-based SL/TP, spread filters, trailing stops, build 5830 compatibility ✅ FXDreema visual EA builder: strategy conversion & export fixes ✅ TradeLocker / Backtrader strategy scripts ✅ Trading bots: Python + MT5 / Binance / Zerodha Kite APIs ✅ IBKR / NinjaTrader automation: TradingView webhooks, live order routing ✅ Risk management automation & position sizing tools 📊 Recent work (no names, real results): ▪ Pine Script S2 Zone Pyramid: 73.7% win-rate with HTF confluence filter (v3, 2-month live XAU/USD data) ▪ MT5 EA: live strategy with ATR trailing, daily loss cap, session filter, spread filter ▪ Signal Bot: TradingView webhook to AWS EC2 to Telegram alerts (live, FastAPI) ▪ Python backtest: XAUUSD 24-month run, PF 1.4+, drawdown under 18% 🧠 Why me: ▪ Active trader (Gold XAU + Crypto): I trade what I build ▪ 19 completed Upwork projects, 271 hours, 100% Job Success ▪ Surat-based, English fluent, fast turnaround 💬 Free 15-min discovery call before any project. Tell me your trading idea, and I'll tell you exactly what's possible and what it'll cost.

I am an expert Quantitative Developer / Analyst with 7+ years of working experience in Hedge Funds. I have a solid background in Software development (15+ years) and extensive experience with data-related projects (10+ years) My experience includes the following: * working with all kinds of asset types: Equities, Options, Futures, Options on Futures, and Crypto. * developing different systematic trading strategies, including intraday, futures, options strategies, arbitrage, etc. * using ML in quantitative projects, like sentiment analysis. * working with dozens of different data APIs, from Yahoo Finance to Bloomberg * building custom dashboards/web apps with Plotly Dash / R Shiny. * building highly scalable cloud infrastructures in AWS. * deriving trading signals from vast amounts of open data. I'm one of the top-rated Pine Script Developers with 20k+ followers on TraidngView: QuantNomad The technological stack includes but is not limited to the following: Programming Languages: Python, R, Pine Script, EasyLanguage, C++ Backtesting engines: Vectorbt, Backtrader, selfmade option/future engines. Databases: PostgreSQL, MongoDB, Redshift, DynamoDB, Cloud Solutions: Amazon AWS, Microsoft Azure. Tools: Git, JIRA, Confluence. OS: Windows, Linux.

Hello! I'm a Quantitative Trading Systems Developer with 10 years of experience in algorithmic trading, financial data science, and market behavior modeling. I specialize in building robust Pine Script strategies for TradingView, predictive models for market trend forecasting, and backtested trading logic for real-time execution. 🔹 Strategy Design & Pine Script Development 500+ PineScript strategies built with multi-timeframe logic (M15–D1) Focus on low drawdown, real-time signal quality, and adaptive take-profit/stop-loss logic Market regime filtering using ADX, RSI, Bollinger Bands, EMA, and price action filters 🔹 Predictive Modeling & Forecasting Systems Created trend forecasting models using TCN-LSTM + Attention, achieving 66–68% accuracy on out-of-sample BTC/USDT data Full data pipeline design: OHLCV ingestion, feature engineering, normalization, and deployment Real-time prediction delivery via Telegram or custom dashboards 🔹 Quantitative Analysis & Risk Modeling Built statistical models for volatility, regime shifts, and position sizing Applied walk-forward testing, recovery factor tracking, and out-of-sample validation Delivered models with performance in mind: not just backtested, but market-ready 💼 Tools & Stack: Python • Pine Script • TSLab • Backtrader • Pandas • NumPy • TA-Lib • MetaTrader 5 APIs • TensorFlow • PyTorch I'm also experienced in reinforcement learning and custom RL environments for trading, but these services are available only to institutional clients. Let's work together to build powerful and reliable trading systems that perform in real-world conditions. Message me if you'd like to discuss your project.

I am a highly creative data scientist / quantitative finance analyst / algorithmic trading developer with a solid background in engineering, mathematics, statistics, machine learning, data and signal processing, physics and technology development. I have expertise in backtesting and strategy development with BackTrader, QuantConnect and Trade Ideas. I program fully automated and robust stocks, ETF, Forex, options, cryptocurrencies and futures trading strategies. I can help you develop or code your custom trading bot, algorithm/robot in Python with execution through the Interactive Brokers IB TWS API. I can deploy an algorithm developed and backtested on QuantConnect to the following brokerages: Interactive Brokers, TD Ameritrade, Tradier, Trading Technologies, Bloomberg, Oanda, Zerodha, Binance, Coinbase, Kraken and Bitfinex. I can develop and backtest option trading strategies on OptionAlpha and OptionOmega. If you need to analyze or gather market data, I have experience with several data provider's API and can customize and automate your analysis with Python scripts, Google Sheet and Excel. I can also create custom scripts and indicators in TradingView as well as sending and trading alerts through Webhooks. I have good communication skills plus acute attention to detail, and strong self-motivation. I look forward to working with you!

Hi! I'm an Industrial Engineer and Data Specialist with a proven track record of building production-grade solutions for the financial markets. I spent significant time working as a Software & Data Engineer for the Argentinian Stock Market. There, I designed and deployed high-performance algorithms, data pipelines, and automation tools that process market data in real-time. If you are looking to automate a trading strategy, backtest an idea with statistical rigor, or build a scalable data pipeline, I can bridge the gap between financial logic and high-performance engineering. What I can help you with: 🔹 Algorithmic Trading: Strategy automation, backtesting, and API integrations (Binance, Interactive Brokers, MetaTrader, etc.). 🔹 Data & Analytics Engineering: Reliable ETL/ELT pipelines, data modeling, and real-time data streaming. 🔹 Advanced Automation: Web scraping, cloud infrastructure setup, and process optimization. My Tech Stack: 🗡️ Python (Pandas, NumPy, Backtrader, CCXT, Asyncio) 🗡️ Data Engineering: DBT, Airflow, Spark 🗡️ Cloud: AWS / GCP 🗡️ Databases: SQL (PostgreSQL, BigQuery, Snowflake) 🗡️ Optimization: Machine Learning, Mathematics, Statistics & Algorithms 🗡️ Visualization: PowerBI / Looker Studio My problem-solving skills are top-notch, and I always strive to provide creative, secure, and highly efficient solutions. Let's talk !