Director, Quantitative Analyst

Position Description:

Develops, implements, and scales multi-asset, open-architecture investment solutions for intermediary clients, using Python, R, and SQL. Measures, monitors, and evaluates investment risks for multi-asset class portfolios using programming languages -- R, Python, MATLAB, Excel, and SQL-- and analytical and database tool Barra. Develops highly scalable investment processes and assists with portfolio management for custom model portfolios.

Primary Responsibilities:

• Develops custom model portfolios that span the spectrum from rule-based to those resulting from complex optimization or factor-based considerations.
• Builds robust quantitative tools to aid all aspects of portfolio analysis, construction, evaluation, and management.
• Develops, articulates, and communicates investment recommendations supported by a comprehensive and evidence-based research process.
• Provides risk analytics and analyzes portfolio exposures to coordinate and evaluate the risk of multi-asset class mandates.
• Conducts advanced modeling of traditional and nontraditional asset classes to construct custom model portfolios.
• Represents the investment team’s investment process and capabilities.
• Recommends investment solutions to existing and prospective intermediary clients.
• Conducts quantitative analysis of information affecting investment programs.
• Collaborates with investment and technology professionals within the division.
• Identifies opportunities for process automation.
• Works with internal teams and external clients to determine scalable design criteria and investment mandates.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Finance, Financial Mathematics, Mathematics, Accounting, Statistics, Business Administration, or a closely related field and six (6) years of experience as a Director, Quantitative Analyst (or closely related occupation) performing investment research or portfolio analytics in Quantitative Analysis and Research, Portfolio and Risk Management, or Portfolio Construction.

Or, alternatively, Master’s degree (or foreign education equivalent) in Finance, Financial Mathematics, Mathematics, Accounting, Statistics, Business Administration, or a closely related field and four (4) years of experience as a Director, Quantitative Analyst (or closely related occupation) performing investment research or portfolio analytics in Quantitative Analysis and Research, Portfolio and Risk Management, or Portfolio Construction.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise ("DE") developing optimization algorithms in Python for multi-asset class portfolio construction; researching macro momentum signals within major asset classes (global equity indices, currencies, and government bonds) for portfolio construction and optimization; analyzing optimization results using quantitative methods (statistical analysis and back testing), historical asset class, and instrument level market data; and performing stress testing following simulations and forward-looking capital market assumptions using Python.
• DE analyzing portfolio performance and risk exposures using SQL Bloomberg Terminal, and Excel to identify and conduct investment investigations; establishing risk framework and threshold system for multiple asset classes using SQL, Bloomberg Terminal, and Excel; and conducting monthly and quarterly risk-factor analysis.
• DE analyzing risk factor model construction and factor definitions and calculations using Barra; translating output statistics using SQL or Oracle Database and Python into meaningful insights for further portfolio construction and risk management; integrating risk models into existing infrastructure using Oracle database and Barra; conducting Barra risk-model implementation and user validation test analysis to enhance the accuracy of risk estimates; and developing automation tools to enhance efficiency in risk analysis, visualization, and workflow optimization.
• DE performing data management of investment and portfolio risk data using SQL or Oracle Database, and Python; designing and building Python data quality checking tools; performing business, systems, and data analysis, process design, and acceptance testing for investment analytics projects using Oracle database; creating and enhancing risk data governance processes, including daily market and liquidity data automated health check dashboard analysis using Python; and providing real-time data visualization and key metric displays using Python.

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Fidelity’s hybrid working model blends the best of both onsite and offsite work experiences. Working onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most hybrid roles require associates to work onsite every other week (all business days, M-F) in a Fidelity office.