Position Description:
Performs software development to expand and improve technical and data infrastructure, research platforms, diagnostic tools, and reporting capabilities associated with multi-factor model risk forecasting, quantitative alpha models, big data analytics, and performance attribution. Participates in the continued development and incorporation of non-traditional and unstructured data, as well as data science applications to enhance the research and investment process. Runs capabilities at scale using Quant Platform capabilities (back-testing), computing core statistical measures, and Cloud Technologies.
Primary Responsibilities:
Coordinates production data management, model integrity, and end-to-end technical support for portfolio management, risk models, and quant research platforms.
Provides analytic solutions and reporting frameworks to partners and senior leaders across the organization.
Delivers innovative data visualization and analytic tools capable of illustrating point-in-time and time series investment themes, portfolio exposures, and factors driving fund performance.
Provides oversight, maintenance, quality assurance, and operational support of analytic and reporting environments to ensure timely and accurate investment intelligence is delivered for direct use within the portfolio management process.
Oversees daily, weekly, and monthly production reporting cycles across the analytic environments.
Ensures all required input data is available, processes run successfully, statistical output is accurate, and reports are generated properly.
Responds to ad-hoc data analysis requests in support of projects performed by equity, fixed income or multi-asset class Quant Analysts.
Develops new processes, performs calculations, identifies anomalies, and produces new reporting capabilities.
Contributes to complex projects within a fast-paced environment.
Liaises with investment professionals to gather requirements and achieve deliverables of technical development teams.
Education and Experience:
Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Mathematics, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Manager, Quantitative Data Analytics and Insights (or closely related occupation) performing quantitative investment research in a fixed income investment domain.
Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Mathematics, or a closely related field (or foreign education equivalent) and one (1) year of experience as a Manager, Quantitative Data Analytics and Insights (or closely related occupation) performing quantitative investment research in a fixed income investment domain.
Skills and Knowledge:
Candidate must also possess:
Demonstrated Expertise (“DE”) performing advanced data analysis for security-level analytics and fixed income products, using Bloomberg data (price, yield, Option-Adjusted Spread (OAS), Option-Adjusted Duration (OAD), and valuation); and performing data validation and model enhancements, and providing advisory services for fixed income market data operations, using python packages (Pandas, SciPy, and Matplotlib).
DE performing stress test simulation for money market funds (asset backed secured and unsecured bonds) in accordance with Rule 2a-7, using Python (XLWings or OpenPyXL) for data interaction and Excel VBA to generate NAV results under various redemption and liquidity scenarios.
DE developing performance attribution factor analysis tools for Fixed Income Funds, using R-Shiny, Python-Flask, or Django (as the back-end) and Dash-Plotly, Angular, or Reach (as the front-end); developing Application Programming Interfaces (APIs) for seamless analytics data retrieval from platforms (Bloomberg); and creating interactive web dashboards to present asset performance insights, using R-Shiny, Python-Flask, or Django.
DE developing index rebalancing and validation (daily and monthly) processes according to methodology rules; developing factor risk models for funds to analyze risk and inform sector allocation, using Statsmodels python package and SciKit-learn; and generating client-facing reports and incorporating what-if scenario analysis (to support investment strategies).
Salary: $131,082.00 to $141,000.00/year.
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Certifications:Category:Data Analytics and InsightsMost roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite 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.
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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.
