Principal Quantitative Developer

Fidelity Investments•Jersey City, NJ

11h•$174,000 - $181,000•Onsite

About The Position

Develops reliable and scalable systems that support investment research and decision‑making across the organization. Designs and enhances applications that bring quantitative insights to portfolio managers and analysts, ensures tools are easy to use, well‑supported, and aligned with business needs. Develops and maintains high‑quality API integrations, data pipelines, and cloud‑based systems to support advanced quantitative research. Ensures systems and applications adherence to software engineering best practices, including code reviews, continuous integration/continuous deployment (CI/CD), and automated testing. Troubleshoots and resolves production issues, ensuring high system reliability, data integrity, and operational excellence. Uses analytical and problem‑solving skills to assist in building and maintaining models that guide investment strategies. Supports the creation of automated processes and modern workflows that improve efficiency, data accessibility, and the overall quality of research. Implements automated testing through unit‑testing frameworks and test‑driven development methodologies to ensure reliability and model integrity.

Requirements

Demonstrated Expertise (“DE”) validating quantitative models by building test cases in multiple scenarios and verifying model parameters against existing documents; establishing and configuring reasonable assumptions in testing case; and verifying model updates by running regression testing.
DE developing and researching portfolio risk analytic metrics on fixed income products using Python and R; and building portfolio level assumptions on a pool of assets (correlation, covariance, volatility, and industry classification of assets) using Python.
DE designing and delivering scalable quantitative research applications to support investment decision‑making by collaborating with quantitative researchers and portfolio teams to translate analytical requirements into production‑ready tools; architecting user‑focused solutions that improve research efficiency, model transparency, and data accessibility; and integrating statistical techniques and investment insights into reliable software used across portfolio construction, optimization, and risk analysis.
DE developing end‑to‑end analytical and research workflows in a technology‑driven investment environment by creating automated data processes and cloud‑based research pipelines; enabling systematic model development through clean data design, structured research frameworks, and reproducible analytical environments; and enhancing research platforms with intuitive interfaces, reusable components, and robust engineering practices aligned with organizational technology standards.

Responsibilities

Analyzes and implements systematic investment strategies including time-series forecasting, multi-asset portfolio construction, risk management frameworks, alpha research, and simulation-based algorithms.
Translates research concepts into production-ready software solutions across the full software development lifecycle.
Analyzes business and research requirements to design scalable, maintainable, and performant quantitative systems.
Evaluates and applies emerging quantitative methodologies, analytics techniques, and industry trends to enhance investment capabilities.
Provides domain expertise across asset classes including equities, fixed income, or alternative investments.
Assists research teams in developing new quantitative models, tools, and products to strengthen competitive positioning.
Partners with cross-functional teams, including Product, Engineering, and Investment Research, to define requirements and deliver end-to-end solutions.
Contributes to long-term architecture planning, system modernization initiatives, and technology roadmap development.
Communicates complex quantitative concepts, system designs, and analytical results to technical and non-technical stakeholders.
Mentors junior team members.