NumPy Jobs

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...

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 ...

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...

I need a clear, well-structured Python pipeline that ingests JPEG road images and their corresponding lane-segmentation masks (they sit in two separate folders sharing the same filenames) and returns one scalar per frame: a normalized lane-visibility score. The number is meant for relative comparison only, so internal units do not have to match any physical standard—just remain self-consistent frame to frame. The logic I have in mind revolves around four cues: • Brightness of the lane pixels themselves • Contrast between those pixels and adjacent pavement pixels • A distance weighting that values pixels closer to the camera more heavily than distant ones • A continuity penalty that reduces the score when the mask reveals breaks or flicker in the lane lin...