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: Conduct comprehensive quantitative/statistical research and analysis and apply market intuition to enhance the monetization of alpha models. Utilize advanced quantitative techniques to research, develop and execute experiments that analyze and predict the impact of financial market trading activities on market dynamics and counterparties. Employ advanced machine learning methodologies to refine and improve execution strategies, ensuring optimal trade outcomes. Research, design and develop innovative quantitative financial models tailored for short trading horizons, focusing on precision and adaptability. Use expertise in computer science to develop high-reliability, production-quality computer code to support financial tools and enhance portfolio management processes through rigorous quantitative research/analysis and continuous optimization. Engage in advancing existing quantitative research initiatives and exploring new avenues for financial research, contributing to the company's competitive edge. Present findings and insights from quantitative research efforts, generating reports for internal stakeholders and driving informed decision-making.
Minimum education and experience required: Master’s degree or the equivalent in Electrical Engineering, Computer Science, Mathematics, Applied Mathematics, Statistics, or a related field. Position does not require specific years of experience but requires listed skills.
Skills required: Must have demonstrated knowledge with Python libraries including numpy, scikit-learn, and pandas for handling, analyzing, and performing statistical data analysis on large (300-500 GB) datasets. Must have demonstrated knowledge of statistical significance and probability theory. Must have demonstrated knowledge of mathematical tools, including linear algebra, multivariate calculus, and random processes. Must have demonstrated knowledge with writing production-level software code in Python and C++, Java or Rust. Must have demonstrated knowledge with developing investment trading strategy and researching pipeline management and performing benchmark risk research. Must have demonstrated knowledge with automation techniques that enhance efficiency and expedite daily operations. Must have demonstrated knowledge with researching, designing and implementing machine learning models used for predictive analytics and model development. Must have demonstrated knowledge with data distribution characteristics and identifying similarities between different data distributions. Must have demonstrated knowledge with approximation algorithms to accelerate computational processes, managing trade-offs in accuracy. Must have demonstrated knowledge with version control software, including git. Must have demonstrated knowledge with Linux/Unix operating system and bash scripting. Must pass company’s required skills assessment. Employer will accept any amount of experience with the required skills.
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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