Quantitative Researcher

Job Description

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: Apply quantitative/mathematical/statistical data analysis and machine learning techniques to research, analyze, formulate, and design sophisticated financial quantitative/mathematics-based models. Research and use data from company disclosures and related sources to build returns forecasting models that can value companies based on economic fundamentals. Research and develop production-quality, high-reliability, highly tuned numerical code based on quantitative research and analysis for data insertion and visualization pipelines, and to implement predictive quantitative/computational/mathematical models used by company for financial trading purposes. Minimum education required: Bachelor’s Degree in Mathematics, Statistics, Computer Science, or related quantitative field. Skills required: Must have knowledge of the following quantitative skills and technologies: P&L analysis of global equities trading strategies; financial, mathematical, and quantitative analysis of P&L attribution, risk scenarios, and model performance; complex, multidimensional systems represented through “big data” problems; quantitative models development and fine-tuning for both theoretical and real-world systems; running and analysis of computer simulations; statistical analysis on data sets across different electronic markets, alternate data sources, and derived trading data; Time Series Analysis of market return data and predictive features (including measures from company financial reports) to understand and model concepts including trends, stationarity, seasonality, and auto-correlation; numerical optimization, Regression Analysis, and statistical inference as applied in quantitative research to understand correlations, multi-collinearity, and power of predictive features; Machine Learning techniques including tree-based and neutral-network-based methods to discover non-linear interactions between predictive features and fitting models; quantitative research methods used in finance, including hypothesis formulation, hypothesis testing, rigorous in-out-sample methodology, and ability to write up results; object-oriented programming in Java or C++; distributed computing including parallel computing; data analysis in R and Python; data science libraries including pandas and NumPy; data science programming environments including Jupyter notebook; data structures and algorithms; source control systems (Git); and Unix/Linux environments. 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. #LI-DNI