Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

Position Description:

Conducts research to mitigate portfolio exposure to risk factors including equity beta and duration within a multi-asset and liability-driven investment context. Builds robust quantitative tools to support all aspects of portfolio construction. Monitors, measures, and attributes portfolio risks and returns. Assists with the implementation of multi-asset class portfolios. Develops Python code to implement financial models that drive global market asset allocation and security selection. Creates web-based tools and dashboards using Python and Dash to visualize fund performance and risk metrics. Performs attribution and risk analysis on managed fund performance.

Primary Responsibilities:

• Conducts research on strategic design and active allocation, from initial concept through full implementation.
• Understands, maintains, and improves infrastructure that supports the 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 investment and technology professionals within the division.
• Provides insights and investment recommendations that are based on quantitative analysis.
• Assists in domestic and international multi asset class research.
• Supports multi-account portfolio construction processes.
• Establishes and tests optimal investment strategies and conducts risk analyses to ensure successful transitions.
• Provides insights and investment recommendations based on quantitative analyses.
• Collaborates with portfolio managers and develops analytics studies using new strategies.
• Supports and tests strategies related to investment and portfolio construction.
• Develops investment action plans based on thorough financial analysis.
• Conducts quantitative analysis of financial data and investment programs, including business valuations for public and private institutions.

Education and Experience:

Bachelor's degree in Accounting, Economics, Finance, Statistics, Mathematics, Financial Engineering, or a closely related field (or foreign education equivalent) and three (3) years of experience as an AM Quantitative Analyst I (or closely related field) performing quantitative analysis to support portfolio management within an asset management and investment products environment.

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

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise ("DE") performing research for tactical asset allocation models and developing long-term strategic asset allocation benchmarks for new products, using Python; implementing Black-Litterman based models for multi-asset portfolio construction using Gurobi; performing factor modeling focused on carry and valuation, including extended credit strategies in emerging market debt, leveraged loans, and high yield, using Pandas and NumPy; and developing capital market assumptions and integrating them into allocation frameworks, using Python.
• DE monitoring and reporting portfolio risk using empirical and Barra-based factor models in Python and R; modeling currency risk using non-USD numeraires, implementing currency risk hedging with synthetic assets, and applying derivative building blocks to expand the hedging platform, using Python, R and SQL; developing empirical risk models and API tools for ex-post risk attribution, integrating dynamic factors, historical currency exposures, and tracking error decomposition in Python and JSON; and constructing pension portfolios to hedge liability duration and risk, using SQL and R.
• DE conducting bottom-up research on multi-asset building blocks for alpha signal development; designing long and short equity strategies; building back-testing infrastructure for equity and credit portfolios using Python; developing sentiment-based signals using Natural Language Processing (NLP) and Machine Learning (ML) techniques (Natural Language Toolkit (NLTK) and PyTorch); implementing constrained portfolio optimization and risk attribution using Convex Optimization (CVXOPT) and Gurobi; and running optimizers with turnover limits, risk constraints, and tradability adjustments using mixed-integer optimization to simplify portfolio implementation in Gurobi.
• DE collaborating with quant developers for production deployment in Autosys using cloud-based environment (AWS); implementing Extract, Transform and Load (ETL) pipelines and multiprocessing framework for data processing, using JavaScript Object Notation (JSON); and modernizing legacy code in MATrix LABoratory (MATLAB) and migrating to non-proprietary languages for improved readability and maintainability, using Python.

Salary: $145,000.00 to $175,000.00/year.

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Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:

Category:

Investment Professionals