Job Description:

Position Description:

Partners with fundamental Equity portfolio managers to provide quantitative alpha generation, portfolio construction, and risk management analytics. Develops customized quantitative tools using programming tools — Python or R. Conducts sophisticated financial modeling using financial packages and portfolio management tools — FactSet and Bloomberg. Conducts research on new factors and data sets, evaluating new risk models, running portfolio optimizations, or providing research to fund managers through portfolio analyses or empirical studies. Delivers innovative data analytics to illustrate current and time series investment themes, portfolio exposures, and factors driving fund performance.

Primary Responsibilities:

• Applies advanced financial analytics and quantitative concepts to support investment needs.

• Creates quantitative stock selection models through idea generation, rigorous empirical analysis, and backtesting to enhance the investment processes of fundamental portfolio managers.

• Investigates techniques to improve portfolio construction and optimization, evaluates risk characteristics, and conducts portfolio analysis and attribution.

• Monitors all aspects of portfolio risk including model construction, factor and covariance definitions, factor calculations, and translating output statistics into meaningful information used within the portfolio management function.

• Responds to ad-hoc data analysis requests.

• Evaluates and implements alternative and/or unstructured data and data science applications to augment the research and investment process.

• Helps fundamental investors understand how various market environments influence the impact of quantitative factors on fund performance.

• Actively contributes to the team's research agenda and takes responsibility for research projects, as well as publishes and distributes research internally.

Education and Experience:

Master's degree (or foreign education equivalent) in Quantitative and Computational Finance, Financial Mathematics, Computer Science, Mathematics, Accounting, Engineering, Statistics, or a closely related field and three (3) years of experience as an AM Quantitative Analyst II (or closely related occupation) conducting quantitative alpha research, risk analytics and portfolio construction for equity investment strategies.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise ("DE") developing factor backtesting frameworks and data visualization and analytics tools to analyze investment risk and return metrics using R, Python, and SQL; and implementing complex investment risk calculations on fund's daily holdings and factor exposures using matrix-math to calculate measures — specific risk, correlation, covariances, tracking-error (TE), volatility, and fund performance attribution analysis.

• DE building equity quantitative models — regression, cross-sectional, time series, NLP in Python and R, using third party structured and unstructured data — to make recommendations for alpha generation and portfolio construction and to enhance investment decision-making by fundamental portfolio managers.

• DE performing simulations and optimizations to evaluate alpha signals, build portfolio strategies, and measure portfolio risk exposures, and curating large data sets using programming languages and financial software — FactSet, Bloomberg, MSCI Barra, Axioma, and Gurobi.

• DE developing written and oral presentations to deliver recommendations to fundamental investors, communicating complex quantitative findings, presenting feedback on methodology, and describing and documenting edge cases.

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Certifications: