Associate, Global Markets FX Options Trading

Analyze market trends and predict price movements in the FX Options space using statistical analysis, machine learning techniques and algorithmic trading platforms. Develop and implement FX Options trading strategies based on statistical analysis and risk management principles, optimizing trading algorithms to maximize profitability and minimize risks. Execute trades, quote client trade requests, actively hedge the risks and ensure all trades adhere to regulatory guidelines. Monitor market data and signals in real-time to identify trading opportunity and manage risk exposure. Collaborate with sales and research to provide data-driven market insights and recommendations to clients and other stakeholders. Collaborate with quantitative analysts and developers to enhance Excel and Python-based trading tools and systems. Requirements:Masters Degree in Financial Engineering, Applied Mathematics, or Quantitative Finance, plus two years of experience in the position offered or as Credit Risk Analyst or Associate in investment banking.* *All of the required experience must have included understanding risk management across multiple U.S. products including FX, equity, rates, repo (UST, Corp Bonds and MBS) and prime brokerage (equity swap); building and automating financial models (including machine learning models) in Python; building post-trade monitoring tools to govern collateral risk profile, such as margin monitors and exposure dashboards; providing quantitative counterparty analysis and conducting risk exposure analysis for financing and derivative trading, including VaR/cVaR margin and bilateral margin rules; conducting stress analysis and back testing; researching and analyzing market trends to understand and mitigate risks, including geopolitical, market and credit risks; and explaining complex results to technical and nontechnical stakeholders. This role entails hybrid work, with time split between working in our New York, NY office and flexibility to telecommute from another U.S. location. #LI-DNI To apply: E-mail rsum to: [email protected]. Ref. #01621.