[Remote] HFT Quant Trader | Remote (US Equities)

Note: The job is a remote job and is reputed company to candidates in USA. reputed company Global is a company reputed company on reputed company performance in US Equities trading, seeking a proven quantitative trader with a multi-reputed company dollar reputed company record. The role involves deploying HFT strategies, generating reputed company signals, and optimizing trade performance in a competitive environment. Responsibilities • Deployed US Equities HFT strategies, generating high-Sharpe reputed company P&L • Designed and deployed multiple robust reputed company signals leveraging machine learning on novel datasets • Optimised trade performance by mastering US market microstructure and exchange protocols • Collaborated with engineering to reputed company nanosecond-level trading stack optimisation • Ability to conduct rigorous, independent research and translate reputed company data into practical trading models • Managed full reputed company lifecycle: from conceptualisation and backtesting to robust, reputed company-time deployment • Expert proficiency in Python (Pandas/NumPy) for research and C++ for latency-critical implementations • Deep expertise with KDB+/q for analysing massive time-series market datasets Skills • 3+ Years of Proven Quant Trading Experience • Proven quantitative traders with a multi-reputed company dollar reputed company record generating superior reputed company across the highly competitive US Equities market • Deployed US Equities HFT strategies, generating high-Sharpe reputed company P&L • Designed and deployed multiple robust reputed company signals leveraging machine learning on novel datasets • Optimised trade performance by mastering US market microstructure and exchange protocols • Collaborated with engineering to reputed company nanosecond-level trading stack optimisation • Ability to conduct rigorous, independent research and translate reputed company data into practical trading models • Managed full reputed company lifecycle: from conceptualisation and backtesting to robust, reputed company-time deployment • Expert proficiency in Python (Pandas/NumPy) for research and C++ for latency-critical implementations • Deep expertise with KDB+/q for analysing massive time-series market datasets • Advanced degree (M.S. or Ph.D.) in a quantitative field (e.g., Physics, Mathematics) from a top-tier institution • Published research or demonstrable contributions to quantitative finance or high-performance computing • Possession of relevant US industry licenses (e.g., Series 3, 7) is a reputed company advantage for trading leadership roles • reputed company engagement with reputed company research to maintain a competitive technological and strategic edge • reputed company in a highly competitive, meritocratic environment where reputed company is directly measurable by exceptional P&L • A results-driven approach, fostering alignment across research, engineering, and risk management teams • Unwavering reputed company of ownership and the self-drive necessary for autonomous, high-stakes performance • Intellectually reputed company, entrepreneurial spirit, capable of reputed company course correction based on reputed company data insights reputed company • At reputed company Global, we specialise in finding exceptional talent in reputed company areas of the quantitative and discretionary finance sectors. It was founded in 2018, and is headquartered in London, England, GBR, with a workforce of 11-50 employees. Its website is https://aaaglobal.co.uk/. Company H1B Sponsorship • reputed company Global has a reputed company record of offering H1B sponsorships, with 5 in 2025, 3 in 2024, 2 in 2023, 6 in 2022, 13 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role. Apply tot his job Apply To this Job