Job Description
Company Overview: A multi-strategy, multi-manager investment platform founded in 2008, focuses on global investment strategies and is seeking a candidate to join its investment teams. The role involves contributing to trading, risk management, alpha generation, and infrastructure development. Job Responsibilities: Assist in developing and validating quantitative models for pricing, volatility modeling, and risk assessment of equity options. Analyze large sets of market and historical data to identify trends, inefficiencies, and opportunities for model or strategy improvement. Support ongoing research into equity options strategies, including volatility surfaces, skew analysis, and implied correlation modeling. Help design and perform backtests for trading strategies and risk management tools using real and simulated data. Develop and maintain analytical tools and dashboards in Python to help traders and researchers visualize performance metrics and model outputs. Work closely with quantitative researchers, traders, and risk teams to translate research insights into practical applications for the trading desk. Qualifications: Strong proficiency in Python, including experience with libraries such as pandas, NumPy, SciPy, and matplotlib. Solid understanding of options theory, including the Black-Scholes model, Greeks, implied volatility, and volatility surfaces. Excellent quantitative and analytical skills with a strong ability to work with large datasets and complex models. Familiarity with financial data providers and experience with backtesting frameworks or quantitative research platforms is desirable. Knowledge of other programming languages, such as SQL, R, or C++ is an advantage. Compensation: Salary: $200,000 – $200,000, Plus Bonus The post Quant Researcher / Developer appeared first on Landing Point.