Job Location: 100 Avenue of the Americas, New York, NY 10013

Note: Company “Hybrid” work attendance policy: In-office work attendance required at the aforementioned office address for collaboration days based on each team’s requirement; telecommuting/working from home is permissible for remainder of the same month.

Duties: Conceptualize, research, analyze, and formulate innovative quantitative investment strategies across a diverse array of financial derivatives including equity futures, interest rate swaps, global bonds, credit derivatives, foreign exchange instruments, commodity futures and various types of options in global markets. Collect, preprocess and transform raw data by applying statistical and signal processing techniques including complex linear algebra, regression methods, time series methods, Bayesian statistics, neural networks, and stochastic optimizations to structure the data optimally for integration into quantitative investment models. Use advanced quantitative modeling, machine learning algorithms, optimization techniques, and rigorous statistical analysis skills to conduct research, design, and develop sophisticated quantitative/mathematics-based models that make financial investment decisions autonomously. Perform mathematical/statistical simulations to evaluate quantitative predictive models using advanced and specialized computational mathematical modeling techniques and numerical methods. Develop and implement systematic models with production-grade coding ensuring a high degree of reliability, efficiency, and scalability suitable for deployment in professional financial environments. Research and develop quantitative/computational libraries of flexible, high-reliability, highly tuned numerical code using knowledge of probability and statistical learning to increase quantitative researcher efficiency across the firm.

Minimum requirements: Master’s Degree in Mathematics, Statistics, Financial Engineering, Computer Science, or related quantitative field plus 3 years of experience in Quantitative Analyst type(s) of positions.

Alternative minimum requirements: Bachelor’s Degree in Mathematics, Statistics, Financial Engineering, Computer Science, or related quantitative field plus 5 years of experience in Quantitative Analyst type(s) of positions.

Skills required: Must have experience using the following quantitative skills/technologies: financial derivatives including futures and forward contracts, interest rate swaps, credit default swaps, and options; understanding of how and where various financial instruments are traded, including product-specific attributes including liquidity, seasonality, and costs to trade; data analysis skills including ability to identify, visualize, and validate statistical patterns in large financial and nonfinancial datasets; metrics used to evaluate systematic investment strategies including Sharpe ratios, drawdowns, and correlations; statistics including complex linear algebra and linear models, probability theory, pattern recognition, regression methods, time series methods, neural networks, Bayesian statistics, and their applications in real-world data analysis; optimization theory and algorithms including linear and non-linear optimization, convex optimization, stochastic optimization, and their applications in finance; Python and SQL with ability to write highly reliable and efficient computer programs; Linux/Unix operating systems; version control collaboration software (Git, SVN); and machine learning algorithms including elastic nets, neural networks, and tree-based models.

Base salary: The base pay for this role will be between $165,000 and $325,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental, and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications, and experience.




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