Quantitative Performance Analyst

Russell Investments•Seattle, WA

About The Position

Every day, Russell Investments seeks to improve financial security for people. We put clients at the center of everything we do, combining deep investment expertise with innovative technology and data-driven insights to help them achieve better outcomes. Joining the Global Performance & Reporting team within Global Risk, you'll help modernize the investment analytics platform that supports Russell Investments' global products, clients, and investment professionals. We're transforming how investment performance is measured, analyzed, and delivered through scalable technology, automation, and AI-enabled workflows. The Performance Analyst supports the calculation, analysis, and communication of investment performance across a range of products while working with Investment Data, Risk, Technology, Product, Client Service, Portfolio Management, and Engineering to deliver accurate analytics and reporting. This role provides an opportunity to develop strong investment performance and technical skills while contributing to process improvements, automation, data quality, and the modernization of Russell Investments' global performance and reporting capabilities.

Requirements

Bachelor's degree or equivalent coursework in Finance, Mathematics, Statistics, Computer Science, Engineering, Data Science, or a related quantitative discipline.
Foundational experience with Python and an interest in developing automation solutions and internal applications.
Working knowledge of SQL, including joins and basic data manipulation; exposure to CTEs, window functions, stored procedures, or data modeling is helpful.
Strong analytical, written, and verbal communication skills, with the ability to collaborate effectively with others.
Ability to apply analytical thinking and technology to understand problems and support solutions.
Ability to manage multiple priorities, meet deadlines, and maintain strong attention to detail.

Nice To Haves

Relevant experience, internship, or academic project work in investment performance, investment reporting, financial technology, investment analytics, or a related analytical discipline preferred.
Exposure to APIs, relational databases, JSON/XML, version control, or modern software development practices preferred.
Coursework, internship, or experience related to investment performance measurement, attribution, GIPS, or investment reporting.
Exposure to Vermilion, Morningstar Direct, SS&C, Bloomberg, Power BI, or similar investment platforms.
Basic experience with Git/GitHub or collaborative software development practices.
Academic or practical experience developing automation tools, workflow applications, or reporting solutions.
Familiarity with AI-assisted development tools such as ChatGPT, GitHub Copilot, or similar technologies.

Responsibilities

Build knowledge of investment performance measurement, attribution methodologies, benchmark construction, GIPS standards, and regulatory reporting requirements.
Prepare accurate and timely performance analytics and reporting for clients, funds, regulators, GIPS composites, and internal stakeholders, with guidance as needed.
Support research into performance methodologies and contribute to improvements in analytics and reporting quality.
Investigate performance questions, identify discrepancies, and escalate complex issues while supporting the development of practical solutions.
Support the design, development, testing, and maintenance of Python-based applications and automation solutions that simplify business processes and reduce manual work.
Contribute to automated reporting pipelines, reconciliation tools, monitoring solutions, reusable Python libraries, and internal applications that improve operational efficiency.
Write and maintain SQL queries that support investment analytics, reporting, data validation, and automation initiatives.
Assist with integrating enterprise data sources and external platforms through APIs and data exchange technologies including REST, JSON, and XML.
Use approved AI-assisted development tools and modern engineering practices to support solution delivery and team productivity.
Support performance and reporting readiness activities for new client launches and portfolio onboarding.
Collaborate with Investment Data, Risk, Technology, Product, Client Service, Marketing, Operations, Compliance, and external vendors to support reporting and analytical solutions.
Support enhancements to reporting platforms including Vermilion, Morningstar, SS&C, and related reporting ecosystems.
Contribute to the standardization of reporting processes and deliverables to improve consistency and reduce operational risk.
Document business processes, methodologies, technical designs, and operational procedures to support knowledge sharing and governance.
Identify and communicate opportunities to simplify, standardize, and improve performance measurement and reporting processes.
Develop knowledge of investment performance, attribution, financial markets, data management, software engineering, and AI technologies.
Support team initiatives related to reporting modernization, return analytics, automation, and internal application development.
Participate in continuous improvement efforts and suggest practical ways to improve team processes and outcomes.