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Fundamental Equities Quant Researcher | Manhattan, NY, USA | Hybrid
2 months ago
Fundamental Equities Quant Researcher Anson McCade, Manhattan, United States Posted: 4 days ago | Job Type: Hybrid | Employment Type: Permanent | Compensation: + bonus/market leading benefits My client is one of the world's leading multi $bn global alternative investment managers. They are seeking to hire an exceptional Equities Quant Researcher. This team sits at the intersection of fundamental investment approach and quantitative precision and discipline. Teams of quantitative researchers and technologists work together to build and scale one of the largest equities portfolios in the market by optimizing various aspects of the investment, risk management, portfolio construction, and trade execution lifecycle. Teams are small and highly collaborative - each member makes meaningful contributions to the research agenda and direction and has a visible impact on the firm's investments. The Role: The team mixes quantitative disciplines, fundamental insights, and creative problem-solving to drive impact every day with fundamental Portfolio Managers and Analysts across the Equity businesses. Responsibilities: Work directly with stakeholders to make crucial decisions about risk, portfolio construction, and investment processes that will directly impact returns. Conduct research and statistical analyses in the evaluation of securities including portfolio construction, multi-factor modeling, TCA, and Market Impact Modeling. Leverage proprietary tools and data to help PMs improve investment decision-making. Automate discretionary strategies within the relevant equity markets. Requirements: Experience with portfolio construction, risk models, and TCA/transaction cost and market impact models. Demonstrated proficiency in statistical methods and a background demonstrating strong analytical problem-solving skills, including but not limited to engineering, statistical modeling, computer programming, scientific laboratory coursework, or similar independent research or thesis. Prior highly-relevant financial industry experience in quantitative research/analytics, trading research, risk research, or portfolio management. Degree in a relevant and highly-analytical field (mathematics/statistics, finance/economics, engineering, and/or computer science) with a strong academic record from a top-tier university. Experience creating and using algorithms to meticulously investigate and work through large data or error-checking problems. Hands-on scripting experience in Python, R, MATLAB, SQL. #J-18808-Ljbffr
