AM Quantitative Analyst II

Position Description: 

Performs research and development of investment methodologies to manage personalized client portfolios at scale. Focuses on quantitative portfolio construction methods to implement new investment ideas and capabilities in client accounts, bridging product development, fundamental and quantitative research, investment management, and technology. Builds practical and robust quantitative models to aid all aspects of the investment management process.  

Primary Responsibilities: 

• Researches, designs, and prototypes quantitative investment methodologies including portfolio construction, optimization tuning, factor risk modeling, and portfolio quality metrics.  

• Works with portfolio engineers, investment managers, and other research groups to enhance the existing portfolio construction process for single and multi-account investment solutions across retail and workplace clients.  

• Partners with the investment architecture teams and business partners to guide requirements for future platform capabilities. 

• Researches opportunities to improve investment management efficiency and effectiveness across the team (scale and process, client outcomes). 

• Evaluates emerging technologies and portfolio construction techniques with potential to improve investment outcomes.  

• Develops tax-aware personalized multi-account portfolio optimization methodologies for managed clients’ retirement goals. 

• Presents investment views and analytical recommendations to portfolio managers and senior investment management. 

• Maintains and improves infrastructure related to the research investment process. 

Education and Experience: 

Bachelor’s degree (or foreign education equivalent) in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Economics, or a closely related field and five (5) years of experience as an AM Quantitative Analyst II (or closely related occupation) performing portfolio risk management, quantitative investment research, and quantitative platform development within the investment management environment. 

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Economics, or a closely related field and three (3) years of experience as an AM Quantitative Analyst II (or closely related occupation) performing portfolio risk management, quantitative investment research, and quantitative platform development within the investment management environment. 

Or, alternatively, PhD (or foreign education equivalent) in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Economics, or a closely related field and no experience. 

Skills and Knowledge: 

Candidate must also possess: 

• Demonstrated Expertise (“DE”) developing portfolio construction processes and implementing quantitative investment methodologies (tax-ware optimization, tax-loss harvesting, multi-portfolio optimization, and multi-period optimization) and transaction cost models (piece-wise linear and nonlinear quadratic) into Axioma Portfolio Optimizer, using Python and R Application Programming Interfaces (APIs); and creating customized, hypothetical portfolio construction implementation for prospective and existing clients and presenting to portfolio managers. 

• DE designing, developing, and testing multi-factor risk models that incorporate fundamental-based risk factors; designing custom estimation universe and standardization scheme; running weighted least squared regression to address heteroscedasticity; performing diagnostics testing to detect multicollinearity and ensure model validity, using t-statistics, adjusted R-squared, and bias-statistics; and quantifying the ex-ante active risk of machine learning (ML) embedded portfolios, using the custom risk model, investment tool (Axioma APA), Webservices, and Python programming languages.  

• DE researching and developing holding-based Brinson attribution framework for multi-asset class fund-of-fund portfolios, analyzing the underlying beginning-period holdings of the portfolio and attributes returns into Tier 1 asset class level allocation effect, Tier 2 fund level selection effect and interaction effect, using investment and business intelligence tools -- Aladdin Explorer, Bloomberg, and SQL; and evaluating portfolio manager’s active decision making based on the analytics.  

• DE analyzing portfolio positioning, risk exposures, and risk factor decomposition for multi-asset class fund portfolios, using investment and business intelligence tool (MSCI BarraOne), Barra risk models, and Aladdin risk models; generating daily risk surveillance analytics, using SQL and VBA programming languages; and evaluating equity portfolio diversification by running Principal Component Analysis (PCA), using Scikit-Learn in Python and examining the absorption ratio over time. 

#PE1M2 

#LI-DNI