AM Quantitative Analyst I

Position Description: 

Conducts research to hedge portfolio exposures to risk factors like equity beta and duration in a multi-asset class and liability-driven context. Builds robust quantitative tools to aid all aspects of portfolio construction. Monitors, measures, and attributes portfolio risks and returns. Aids in the implementation of equity portfolios. Develops Python code to implement financial models that support global market asset allocation and security selection for investment portfolios. Uses Python and Flask to develop web-based tools and dashboards to visualize fund performance and risk metrics. Performs attribution and risk analysis on the performance of managed funds. 

Primary Responsibilities: 

• Leads research in strategic design and active allocation from inception to implementation. 

• Understands, maintains, and improves infrastructure supports investment process.  

• Builds and automates tools to monitor portfolios for compliance with mandates and risk boundaries.  

• Builds dashboards to help portfolio managers manage client portfolios.  

• Collaborates closely with other investment and technology professionals within the division.  

• Contributes to the investment team’s success with thorough insights and investment recommendations that are based on quantitative analysis.  

• Assists in domestic and international equity research.  

• Supports multi-account portfolio constriction processes.  

• Tests investment strategies and conducts after-tax and risk analyses to ensure successful transitions.  

• Provides insights and investment recommendations based on quantitative analyses.  

• Establishes optimal investment approaches by conducting after-tax and risk analyses.  

• Ensures successful transitions from the Research and Development team to the investment management teams.  

• Collaborates with portfolio managers and develops analytic studies using new strategies.  

• Supports and tests strategies relates to investment and portfolio construction.  

• Prepares plans of action for investment using financial analyses.  

• Conducts quantitative analyses of information involves investment programs or financial data of public or private institutions, includes valuation of businesses. 

Education and Experience: 

Master’s degree (or foreign education equivalent) in Accounting, Economics, Finance, Financial Mathematics, Statistics, Mathematics, Financial Engineering, or a closely related field and no experience. 

Skills and Knowledge: 

Candidate must also possess: 

• Demonstrated Expertise (“DE”) in the development and support of liability driven investment (LDI) strategies for pension plans; performing portfolio construction, asset allocation, and risk management of pension portfolios; hedging liability duration along the yield curve to manage credit spreads; evaluating trade-offs between objectives and constraints to solve optimization problems; analyzing custom funded ratio attribution; working with client-facing teams on what-if scenarios and developing strategic asset allocation models. 

• DE performing research and development of tactical asset allocation models; performing factor modeling with a focus on valuation; developing capital market assumptions and implementing them in asset allocation models; evaluating closed form solutions versus optimizer-based solutions to select appropriate methods for best performance; supporting portfolio managers providing OCIO services to institutional clients; running spend analyses for endowments using Monte Carlo simulations. 

• DE developing tools for optimal asset allocation interfacing with enterprise systems and databases, and presenting charts and metrics as interactive dashboards; using SQL and Python and R to present reports and results of analyses, including using optimizers -- CPLEX or NLopt or CVXOPT to construct portfolios meeting stated objectives and investment constraints;  developing web applications and dashboards to analyze and visualize asset performance, using R-Shiny and Python-Flask/Django (as the back-end) and Dash-Plotly or Angular or React (as the front-end); optimizing the efficiency of back-end applications using multi-threading techniques; and building data visualization tools for end users, using Tableau and Power BI. 

• DE performing Continuous Integration/Continuous Deployment (CI/CD) – deploying apps in Jenkins pipelines and performing code versioning, using GIT and Stash and BitBucket; performing development release -- implementing unit, use case, and scenario tests for software systems using Python Unittest; ensuring the efficient use of software development processes to manage quantitative financial data warehouse using SQL and Oracle DBMS and Snowflake; and managing application deployed in Linux OS on AWS Cloud Infrastructure.