Fidelity will not provide immigration sponsorship for this position.
Job Description:Position Description:
Designs and maintains Python-based data abstraction and analytical tools to streamline and standardize quantitative processes. Responds to ad-hoc data analysis requests in support of projects performed by quant analysts. Contributes to the continued development and incorporation of non-traditional and unstructured data, as well as data science applications, to enhance the research and investment process. Programs in Python or R with the ability to develop customized quantitative tools. Works with FactSet and Bloomberg. Back-tests Quant Platform capabilities. Runs Cloud technologies. Supports production data management and model integrity, and provides end-to-end technical support for portfolio management, risk models, and quant research platforms. Develops quantitative techniques to inform securities investing, equities investing, pricing, or valuation of financial instruments. Develops mathematical or statistical models for risk management, asset optimization, pricing, or relative value analysis.
Primary Responsibilities:
- Conducts investment risk forecasting and portfolio construction, including model construction, factor definitions, factor calculations, and translates output statistics into meaningful information.
- Develops and operates data platforms to deliver production-grade data curation to be utilized in quantitative models, portfolio construction, and trading.
- Supports production reporting cycles across analytic environments.
- Ensures input data integrity, availability, and completeness; verifies successful process execution, accurate statistical output, and proper report generation.
- Produces new reporting capabilities.
- Works with quantitative analytics (fund and index performance measurement) and Security Reference data across asset classes and derivative instruments.
- Computes core statistical measures.
- Provides analytic solutions and reporting frameworks to business partners and senior leadership.
- Expands and improves technical and data infrastructure, research platforms, diagnostic tools, and reporting for multi-factor model risk forecasting, quantitative alpha models, big data analytics, and performance attribution.
Education and Experience:
Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Senior Manager, Quant Data Analytics and Insights (or closely related occupation) performing analysis to evaluate portfolio investments against client guidelines and firm compliance controls, using Python, SQL, and R.
Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Manager, Quant Data Analytics and Insights (or closely related occupation) performing analysis to evaluate portfolio investments against client guidelines and firm compliance controls, using Python, SQL, and R.
Skills and Knowledge:
Candidate must also possess:
· Demonstrated Expertise supporting large quantitative platforms as a product owner using Stash; facilitating stand ups, sprint planning, retrospectives, and backlog grooming, using Jira; and writing risk model methodologies and specification documents, interpreting business requirements, and creating analytical visualization solutions, using Confluence and Visio.
· Demonstrated Expertise analyzing security analytics across asset classes, including equities, options, swaps, commodities, and fixed income (including swaps and security types in fixed income including treasuries, corporates, Municipal bonds, and securitized products) using BarraOne or FactSet; covering funds across active, systematic, open and closed architecture asset allocation, and risk modelling, using Bloomberg PORT, MSCI Barra’s equity models, and Barra Multi Asset Class model; and analyzing the Barra Risk Factor Model construction, factor definitions and calculations, and translating output statistics into portfolio management insights, using BarraOne UI.
· Demonstrated Expertise supporting portfolio managers and quantitative analysts by performing portfolio performance and risk reporting, using Oracle SQL, Tableau, and Excel; building and enhancing reports, using Python, R, and Excel VBA; and calculating parametric VaR, duration, Monte Carlo simulations, and stress testing for regulatory purposes, using Oracle SQL, Python, and BarraOne.
· Demonstrated Expertise spearheading design, implementation, or ongoing operations of robust data quality frameworks for financial data systems on multi-terabyte data sets, using SQL, R, and Python; establishing Key Performance Indicators (KPIs) for internal and external vendor teams and driving improvement, using Oracle SQL and Excel; and collaborating cross functionally with development teams to ensure data integrity, enforce data quality checks, and procedures to maintain accuracy and consistency, and implementing automated checks and systems for monitoring, using Autosys, SQL, and Python.
Salary: $145,800.00 to 181,000.00 /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.
Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Skills Required
- Bachelor's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field, plus five years of relevant experience.
- Alternatively, a master's degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field, plus three years of relevant experience.
- Experience evaluating portfolio investments against client guidelines and firm compliance controls using Python, SQL, and R.
- Experience supporting large quantitative platforms as a product owner using Stash.
- Experience facilitating stand-ups, sprint planning, retrospectives, and backlog grooming using Jira.
- Experience writing risk model methodologies and specification documents, interpreting business requirements, and creating analytical visualizations using Confluence and Visio.
- Experience analyzing security analytics across equities, options, swaps, commodities, fixed income, funds, asset allocation, and risk modeling using BarraOne or FactSet.
- Experience using Bloomberg PORT, MSCI Barra equity models, and Barra Multi Asset Class models.
- Experience analyzing Barra Risk Factor Model construction, factor definitions, calculations, and output statistics using BarraOne UI.
- Experience performing portfolio performance and risk reporting using Oracle SQL, Tableau, and Excel.
- Experience building and enhancing reports using Python, R, and Excel VBA.
- Experience calculating parametric VaR, duration, Monte Carlo simulations, and regulatory stress testing using Oracle SQL, Python, and BarraOne.
- Experience designing, implementing, or operating data quality frameworks for financial data systems and multi-terabyte datasets using SQL, R, and Python.
- Experience establishing KPIs for internal and external vendor teams using Oracle SQL and Excel.
- Experience implementing automated data integrity checks and monitoring systems using Autosys, SQL, and Python.
Fidelity Investments Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fidelity Investments and has not been reviewed or approved by Fidelity Investments.
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Strong & Reliable Incentives — Bonuses, commissions, and profit-sharing are presented as generous and meaningful components of total compensation, with certain roles achieving high total earnings through multiple pay streams. Variable pay is consistently framed as a positive contributor beyond base salary.
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Retirement Support — A 401(k) match up to 7% alongside additional profit-sharing up to 10% materially enhances long-term compensation. These retirement features are highlighted as standout strengths of the overall package.
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Parental & Family Support — Generous paid parental leave (16 weeks maternity, 12 weeks parental), backup dependent care, and adoption assistance provide robust family support. Hybrid work and caregiving resources further ease family responsibilities.
Fidelity Investments Insights
What We Do
At Fidelity, our goal is to make financial expertise broadly accessible and effective in helping people live the lives they want. We do this by focusing on a diverse set of customers: - from 23 million people investing their life savings, to 20,000 businesses managing their employee benefits to 10,000 advisors needing innovative technology to invest their clients’ money. We offer investment management, retirement planning, portfolio guidance, brokerage, and many other financial products. Privately held for nearly 70 years, we’ve always believed by providing investors with access to the information and expertise, we can help them achieve better results. That’s been our approach- innovative yet personal, compassionate yet responsible, grounded by a tireless work ethic—it is the heart of the Fidelity way.









