NumPy Jobs

I need an expert in Python to help with data analysis and processing tasks, specifically focused on unstructured data such as text or images. The ideal candidate should be proficient in Python libraries and tools designed for handling unstructured datasets. Your role will involve creating scripts or solutions to extract insights, patterns, or other relevant analyses from the data provided. If you have a strong command over libraries like Pandas, NumPy, or specialized tools for text and image processing, I’d love to hear from you.

Project: Titan-X Prime (Quantitative Options Scalper) Target Environment: Python 3.13 (Free-Threaded/No-GIL) Primary Goal: To capture high-conviction "Gamma Bursts" in Nifty Options while neutralizing the 2026 0.15% STT tax drag through microstructure-based precision. 1. System Architecture (Concurrency Model) The system must utilize a Multi-Threaded Producer-Consumer model to leverage Python 3.13’s true parallelism. • Thread 1 (Ingestion): WebSocket feed for Nifty Spot, Futures, and ATM/Near-OTM Option Chain (±10 strikes). • Thread 2 (Microstructure): Real-time calculation of Weighted Order Book Imbalance (WOBI) every 100ms. • Thread 3 (GEX Engine): Recalculation of Dealer Gamma Exposure (GEX) and Zero-Gamma Level every 60 seconds. • Thread 4 (Ex...

I need help with a Python exercise focused on data analysis. Key tasks include: - Data cleaning/extraction - Visualization/plotting - Statistical analysis Ideal skills and experience: - Proficiency in Python, especially with libraries like Pandas, NumPy, and Matplotlib - Experience with data cleaning and preparation - Strong data visualization skills - Background in statistical analysis

The project is to build a Python-based bot that trades equities on NYSE, NASDAQ, and AMEX. It must run end-to-end without manual intervention: gathering live market data, analysing it in real time, placing orders, and continuously enforcing risk limits. Core functionality • Automated trade execution driven by a configurable strategy engine • Real-time market analysis with fast data ingestion (websocket or streaming API) • Built-in risk management: position sizing, max draw-down and stop-loss rules Technical notes Python is mandatory; common libraries such as pandas, NumPy, TA-Lib, and asyncio are expected. The code should be clean, modular, and ready to plug into broker APIs like Interactive Brokers, Alpaca, or Tradier. A lightweight front-end (CLI or simple dashbo...

I need a seasoned quantitative developer who can turn my Iron Condor options strategy into a fully automated trading BOT for Indian markets. The system must trade exclusively in listed options and operate through the NSE NOW interface, handling everything from order placement and modifications to position monitoring and exit. Core workflow • Pull live option chain data, calculate real-time Greeks, and identify entry prices that satisfy my Iron Condor rules (delta-neutral, predefined distance between strikes, and minimum credit per leg). • Submit simultaneous multi-leg orders via NSE NOW, confirming fills and retrying intelligently if partials occur. • Track open positions tick-by-tick, updating P/L and Greeks so risk controls—max loss, max profit, time-based exits...

I want a production-ready Python algorithm that can scan the Nifty 50 throughout the session, weigh profit opportunities against downside risk, and fire off intraday orders several times a day when the reward-to-risk profile is attractive. Core logic • Fuse three data streams in real time: historical price series, live technical-indicator feeds that you compute on the fly, and sentiment or headline signals drawn from the latest market news. • Use that blended input to generate probabilistic forecasts, then translate those forecasts into position sizing that keeps risk in check while still pursuing upside. • The system must be able to trigger, modify, and exit trades automatically during market hours—no end-of-day batching. I code in Python myself, so please kee...

Ho bisogno di una piccola web app che parta da un file Excel e mi restituisca, in modo chiaro e veloce, la deviazione standard delle colonne che seleziono. Funzionalità essenziali • Caricamento di un file .xlsx tramite interfaccia web. • Riconoscimento automatico dei fogli e delle colonne numeriche. • Selezione multipla delle colonne da analizzare. • Calcolo e visualizzazione della deviazione standard per ogni colonna scelta, con risultato immediato a schermo. Preferenze tecniche (ma resto aperto a proposte migliori) • Backend in Python con Flask o Django, oppure Node.js. • Librerie consigliate: pandas, NumPy o equivalenti per il calcolo statistico. • Front-end semplice e responsivo, anche con Bootstrap. Consegna 1. Codice ...