Senior Systems Analyst

Fidelity Investments•Boston, MA

1d•$80,000 - $153,000

About The Position

Are you ready to shape the direction of how technology enables investment decision‑making at scale? Join a highly collaborative team focused on advancing Investment Research capabilities within Asset Management’s Portfolio Management and Research organization. This role is a senior individual contributor and thought leader, responsible not only for analysis execution but for driving analytical direction across complex, cross‑domain initiatives. You’ll partner closely with senior product, engineering, architecture, and business leaders to ensure technology solutions are scalable, resilient, and aligned to long‑term research strategy. You will play a critical role in enabling Investment Professionals to discover, analyze, and publish research efficiently—providing Portfolio Managers with timely, high‑quality insights that directly inform portfolio construction and alpha generation.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or equivalent experience
5+ years of experience in Systems Analysis or closely related roles
Demonstrated history of owning and driving outcomes for large, mission‑critical initiatives
Strong leadership presence with the ability to influence without authority
Exceptional written and verbal communication skills at both technical and executive levels
Extensive experience as a Systems Analyst on enterprise‑scale, cloud‑based platforms
Strong conceptual understanding of Java‑based architectures, with the ability to reason about system behavior, performance, and integration patterns
Deep hands‑on experience with APIs and service‑oriented architectures, including RESTful design, versioning strategies, and error handling
Advanced SQL proficiency and confidence working with large, complex relational datasets
Strong understanding of modern cloud architectures, event‑driven patterns, and distributed systems
Proven experience operating effectively in Agile at scale, including multi‑team delivery models
Experience influencing test strategy and quality practices, including collaboration on automation approaches (e.g., Playwright)
Generative AI Enablement (Applied Use, Not Model Development)
Strong working knowledge of Generative AI concepts, limitations, and enterprise‑safe usage
Proven experience applying GenAI tools to: Accelerate complex analysis and discovery, Improve clarity and quality of technical documentation, Synthesize large volumes of information into actionable insights
Clear understanding of responsible AI usage, data privacy, and security considerations in a regulated environment

Responsibilities

Provide analysis leadership across large‑scale, highly complex initiatives spanning multiple platforms, domains, and data flows
Operate as a go‑to analyst for ambiguous problem spaces, shaping problem statements and solution approaches before requirements are fully formed
Lead deep systems discovery and architectural analysis, including reverse‑engineering legacy platforms and evaluating modernization paths
Collaborate with product, architecture, and engineering leadership to influence solution design, integration strategy, and roadmap decisions
Translate complex business objectives into clear, scalable technical designs, epics, and high‑quality investment‑ready user stories
Evaluate and define API strategies, data contracts, and service interaction models across internal and external systems
Perform advanced data analysis using relational databases to validate assumptions, uncover risks, and inform trade‑off decisions
Own and curate system‑level artifacts (end‑to‑end flows, state diagrams, interface contracts, dependency maps) used across squads and programs
Act as a bridge between business strategy and technical execution, communicating effectively with senior stakeholders
Apply Generative AI tools responsibly to enhance analysis quality, accelerate synthesis, and improve documentation and decision support
Drive continuous improvement in analysis discipline, tooling, and delivery effectiveness across the organization
Take accountability for end‑to‑end requirement integrity, from early discovery through implementation validation and release readiness