Quantitative Analyst - Derivatives Trading

Our client, a prestigious investment bank, is seeking a highly analytical and mathematically skilled Quantitative Analyst (Quant) to join their cutting-edge Derivatives Trading desk in Los Angeles. This critical role involves developing, implementing, and maintaining sophisticated mathematical models and algorithms used for pricing, risk management, and trading strategies within complex derivative markets. The ideal candidate will possess a strong academic background in a quantitative field and exceptional programming skills.

Key Responsibilities:

Design, develop, and implement quantitative models for pricing and hedging exotic derivatives, including options, futures, and structured products. Develop algorithms for high-frequency trading strategies and portfolio optimization. Conduct rigorous backtesting and statistical analysis of trading strategies and models. Analyze market data to identify trading opportunities and potential risks. Collaborate with traders, risk managers, and other quantitative analysts to refine models and implement new trading ideas. Perform quantitative risk assessment and contribute to the development of risk management frameworks. Write high-quality, production-ready code in languages such as C++, Python, or R. Research and stay current with the latest advancements in financial mathematics, computational finance, and quantitative trading techniques. Contribute to the technological infrastructure supporting the trading desk, including data management and analysis tools. Ensure compliance with regulatory requirements and internal policies.

Required Qualifications:

Master's degree or Ph.D. in a highly quantitative field such as Mathematics, Physics, Statistics, Computer Science, Financial Engineering, or Economics. Proven experience (3+ years) as a Quantitative Analyst in investment banking, hedge funds, or proprietary trading firms, with a focus on derivatives. Strong theoretical knowledge of financial markets, derivative pricing models (e.g., Black-Scholes, Heston), and risk management techniques. Proficiency in programming languages commonly used in quantitative finance, particularly C++, Python, or R. Experience with data analysis and statistical modeling libraries. Excellent analytical, problem-solving, and critical thinking skills. Ability to work effectively under pressure in a fast-paced trading environment. Strong communication and interpersonal skills, with the ability to articulate complex quantitative concepts to both technical and non-technical audiences. Familiarity with machine learning techniques applied to finance is a plus.

This is an outstanding opportunity for a talented quant to work with a leading team in a challenging and rewarding environment.