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: Employ rigorous scientific methods to develop cutting-edge investment models. Analyze a vast array of datasets to uncover actionable investment insights using advanced quantitative techniques, Machine Learning, and statistical models. Create, implement, and rigorously test investment ideas, adhering to best practices throughout the research process. Use quantitative metrics to analyze and evaluate model performance while ensuring the integrity and accuracy of data. Productionize investment models using programming languages such as Python and collaborate with engineers to support the development and maintenance of team-wide platforms that create shareable feature sets and tools. Stay abreast on the latest advancements in Machine Learning and Statistics by reviewing current research papers and attending academic seminars. Utilize advanced mathematical, statistical, and computational skills to research and build state‐of‐the‐art quantitative investment strategies. Research and apply mathematical and statistical principles, quantitative data analysis techniques, computational principles, and market knowledge to large, often novel datasets to assist in the performance of financial predictive analysis. Research, design, develop, and back-test predictive quantitative financial models using advanced statistical learning, machine learning, and statistical data analysis skills in the application of mathematic principles. Apply numerical algorithms, statistical analysis, optimization, and advanced machine learning techniques, including complex linear algebra, regression methods, time series methods, Bayesian statistics, kernel machine techniques, deep neural networks, and stochastic optimization to formulate and design sophisticated financial modeling systems. Develop production-quality, high-reliability, highly tuned numerical code using complex linear algebra, statistical modeling, and numerical optimization to aid in the development of financial predictive models capable of processing, sorting, and comparing vast amounts of data, which will drive investment decisions.

Minimum education required: Master’s Degree in Mathematics, Statistics, Operations Research, or related quantitative field.

Skills required: Must have knowledge of the following quantitative skills: ability to develop and apply quantitative models to supervised prediction tasks; Object-Oriented programming languages (Python) used for writing production-level code for data analysis and model implementation; Machine Learning and statistical techniques including regression analysis, hypothesis testing, and supervised learning, and Machine Learning algorithms (trees, kernel machines, or neural networks); ability to test, define, and deploy quantitative models and software tools; data visualization tools; and ability to design and execute statistics-based tests of model performance to optimize model accuracy and reliability. Must also pass company’s required skills assessment.

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.