Senior Manager, Data Analytics and Insights

Fidelity•Boston, MA

18h•Onsite

About The Position

This position analyzes and builds equity datasets and analytical outputs used across quantitative research, risk modeling, and performance attribution. The role involves calculating and applying a broad range of equity analytics, including portfolio risk, return attribution, EPS, fundamental ratings, and fundamental equity factors. The individual will maintain complex SQL-based transformations, analytical datasets, and factor-model components. Additionally, they will develop diagnostic routines, data-profiling scripts, and integrity checks to ensure computational accuracy and detect anomalies. The role also includes implementing and evolving data domains, model enhancements, and analytical capabilities by architecting ingestion frameworks, integrating vendor datasets, and optimizing environments for high-volume model execution.

Requirements

Bachelor’s degree in Finance, Economics, Business Analytics, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing portfolio risk, return attribution, and equity and data analytics.
Demonstrated Expertise (DE) performing quantitative investment research and financial data analysis, including constructing and analyzing security- and portfolio-level datasets.
DE analyzes and structures earnings-per-share estimates, and analyst forecasts, returns, and active weights, using Python, R, and SQL.
DE conducting portfolio performance attribution and risk analysis, including Brinson attribution, decomposition of portfolio returns, evaluation of benchmark-relative performance, analysis of factor exposures and sensitivities, and measurement of portfolio-level risk metrics (tracking error and beta), using Python, SQL, FactSet Portfolio Analysis Tool, and Barra Portfolio Manager.
DE designing, developing, and implementing advanced analytical tools, data pipelines, and multi-factor models to support stock selections and investment decision making, including data modeling, automation of recurring calculations, validation of inputs and outputs, and building interactive dashboards and visualizations using Python, SQL, Tableau, and Excel.
DE sourcing, validating, and integrating market, fundamental, and reference data to support investment and risk analysis, including working with equity and portfolio datasets, reconciling vendor data, and ensuring data quality and consistency using Bloomberg and FactSet platforms.

Nice To Haves

Master’s degree in Finance, Economics, Business Analytics, Computer Science, Engineering, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Manager, Data Analytics and Insights (or closely related occupation) performing portfolio risk, return attribution, and equity and data analytics.

Responsibilities

Performs end-to-end reporting and analytics operations, ensuring timely, accurate, and reliable delivery of daily, weekly, monthly, and ad-hoc analytical outputs across key business areas.
Ensures data availability, quality, and process stability, monitoring inputs, workflows, and analytical outputs to maintain high standards of data integrity and reporting accuracy.
Responds to complex, ad-hoc analytical requests, providing data-driven insights and support for strategic initiatives, research projects, and leadership priorities.
Develops and enhances analytical tools, dashboards, and visualizations to communicate trends, business drivers, and performance insights to a wide range of stakeholders.
Designs, improves, and automates data and analytical processes, including developing new calculations, identifying data anomalies, and creating new reporting capabilities.
Participates in multiple concurrent projects, assists with planning, prioritization, resource co-ordination, risk assessment, and timely delivery in a fast-paced environment.
Acts as a primary liaison across business partners, technology teams, research groups, and external vendors, ensuring alignment and clear communication throughout the analytics ecosystem.
Troubleshoots and resolves data or technology issues, ensuring continuity in analytical production and delivery of high-quality outputs.
Provides analytical and technical guidance to senior leadership, contributing to strategic planning materials, prototypes, and recommendations.
Mentors and develops junior team members.