Senior Manager, Quant Data Analytics and Insights

Fidelity; San Francisco (CA); On-site; USD 146,000 - 181,000; Full time

Job summary

Fidelity is seeking a Senior Manager, Quant Data Analytics and Insights to design and maintain Python-based data tools for supporting quant research and portfolio management. You will work with FactSet, Bloomberg, Barra, and other platforms to build robust data pipelines and risk models.

You’ll lead data platform development, governance, and reporting for senior leadership, ensuring data integrity and actionable insights in a fast-paced investment environment.

Qualifications

• Bachelor’s or Master’s degree in a related field with required years of analytics experience.
• Proven ability to develop quantitative tools using Python or R and SQL.
• Experience supporting large quantitative platforms and data analytics stakeholders.

Responsibilities

• Conduct investment risk forecasting and portfolio construction with factor models.
• Develop and operate production-grade data platforms for quantitative models.
• Produce analytics and reporting for senior leadership and business partners.
• Ensure data integrity and reliable reporting across analytic environments.
• Expand data infrastructure and diagnostic tools for multi-factor risk forecasting.

Skills

Python

SQL

R

Jira

Confluence

Visio

BarraOne

FactSet

Bloomberg PORT

MSCI Barra

Tableau

Excel VBA

Autosys

Oracle SQL

Stash

Education

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or closely related field

5 years as Senior Manager, Quant Data Analytics and Insights

Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or closely related field + 3 years experience

Tools

Stash

Jira

Confluence

Visio

BarraOne

FactSet

Bloomberg PORT

MSCI Barra

BarraOne UI

Oracle SQL

Tableau

Excel VBA

Autosys

Job description

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 & 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.

Certifications:

Category:

Data Analytics and Insights

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.