Senior Manager, Quant Data Analytics and Insights

Fidelity Investments•San Francisco, CA

3d•$145,800 - $181,000

About The Position

Designs and maintains Python-based data abstraction and analytical tools to streamline and standardize quantitative processes, and responds to ad-hoc data analysis requests supporting quant analyst projects. Contributes to incorporating non-traditional and unstructured data and data science applications into research and investment processes. Programs in Python or R to develop customized quantitative tools; works with FactSet and Bloomberg; back-tests Quant Platform capabilities; and runs cloud technologies. Supports production data management and model integrity, providing end-to-end technical support for portfolio management, risk models, and quantitative research platforms. Develops quantitative techniques and mathematical or statistical models for securities and equity investing, pricing, valuation, risk management, asset optimization, and relative value analysis. This role conducts investment risk forecasting and portfolio construction; develops and operates data platforms for production-grade data curation; supports production reporting; and ensures data integrity and accurate process execution and outputs. It produces reporting capabilities and analytic solutions for business partners and senior leadership, works with performance measurement and security reference data across asset classes and derivatives, computes statistical measures, and improves technical infrastructure, research platforms, diagnostic tools, and reporting for risk forecasting, quantitative alpha models, big data analytics, and performance attribution. The position requires a bachelor’s degree in a specified or closely related field and five years of relevant experience, or a master’s degree in a specified or closely related field and three years of relevant experience. The experience must include analyzing portfolio investments against client guidelines and firm compliance controls using Python, SQL, and R. The role also requires demonstrated expertise with specified quantitative platforms, analytics, reporting, risk calculations, and data quality frameworks. Fidelity states that it will not provide immigration sponsorship for this position. Fidelity is transitioning to a full-time onsite working model through a phased rollout; onsite requirements vary by role and location and may evolve.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent), and five years of relevant experience; alternatively, a master’s degree in one of those fields (or foreign education equivalent) and three years of relevant experience.
Relevant experience must include analyzing portfolio investments against client guidelines and firm compliance controls using Python, SQL, and R.
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 equities, options, swaps, commodities, and fixed income—including treasuries, corporates, municipal bonds, and securitized products—using BarraOne or FactSet.
Demonstrated expertise covering funds across active, systematic, open and closed architecture asset allocation, and risk modeling using Bloomberg PORT, MSCI Barra equity models, and the Barra Multi Asset Class model.
Demonstrated expertise analyzing 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 with portfolio performance and risk reporting using Oracle SQL, Tableau, and Excel.
Demonstrated expertise building and enhancing reports using Python, R, and Excel VBA.
Demonstrated expertise calculating parametric VaR, duration, Monte Carlo simulations, and stress testing for regulatory purposes using Oracle SQL, Python, and BarraOne.
Demonstrated expertise designing, implementing, or operating robust data quality frameworks for financial data systems on multi-terabyte data sets using SQL, R, and Python.
Demonstrated expertise establishing KPIs for internal and external vendor teams and driving improvement using Oracle SQL and Excel.
Demonstrated expertise collaborating with development teams to ensure data integrity, enforce data quality checks, and maintain accuracy and consistency, and implementing automated checks and monitoring systems using Autosys, SQL, and Python.

Responsibilities

Design and maintain Python-based data abstraction and analytical tools to streamline and standardize quantitative processes.
Respond to ad-hoc data analysis requests in support of projects performed by quant analysts.
Contribute to the incorporation of non-traditional and unstructured data and data science applications into the research and investment process.
Develop customized quantitative tools using Python or R; work with FactSet and Bloomberg; back-test Quant Platform capabilities; and run cloud technologies.
Support production data management and model integrity, providing end-to-end technical support for portfolio management, risk models, and quantitative research platforms.
Develop quantitative techniques and mathematical or statistical models for investing, risk management, asset optimization, pricing, valuation, or relative value analysis.
Conduct investment risk forecasting and portfolio construction, including model construction, factor definitions and calculations, and translating output statistics into meaningful information.
Develop and operate data platforms that deliver production-grade data curation for quantitative models, portfolio construction, and trading.
Support production reporting cycles across analytic environments.
Ensure input data integrity, availability, and completeness; verify successful process execution, accurate statistical output, and proper report generation.
Produce new reporting capabilities and provide analytic solutions and reporting frameworks to business partners and senior leadership.
Work with quantitative analytics for fund and index performance measurement and Security Reference data across asset classes and derivative instruments.
Compute core statistical measures.
Expand and improve 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.
Support large quantitative platforms as a product owner; facilitate agile ceremonies and backlog grooming; and write risk model methodologies and specification documents, interpret business requirements, and create analytical visualizations.
Analyze security analytics across asset classes and support funds across investment and asset-allocation approaches and risk modeling.
Support portfolio managers and quantitative analysts with portfolio performance and risk reporting; build and enhance reports; and calculate parametric VaR, duration, Monte Carlo simulations, and regulatory stress testing.
Design, implement, or operate data quality frameworks for financial data systems on multi-terabyte data sets; establish KPIs for internal and external vendor teams; and collaborate with development teams on data integrity, quality checks, and automated monitoring.