Manager, Quantitative Data Analytics and Insights

Fidelity Investments•Boston, MA

7d•$131,082 - $141,000•Hybrid

About The Position

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.

Requirements

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.
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).

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.