Performance & Attribution – Analytics Product Manager, Associate

BlackRock
London, Greater LondonPosted 2 April 2026

Job Description

About this role The Analytics Product team empowers investment and risk management decision‑making for BlackRock and Aladdin clients through industry‑leading models, analytics, research, and processes supporting investor activities. The team delivers value for users, clients, and prospects by reliably meeting commitments. We craft compelling research and applied solutions. Enable new opportunities with fit-for-purpose analytics. Apply extensive confirmed experience across the client lifecycle. In close collaboration with partner teams throughout the Aladdin Business, the team accomplishes the analytics and product development lifecycle with full ownership. We speed up model development and delivery using agile methods. The team leads the deployment of new model features and infrastructure improvements. Encourage adoption within the Aladdin community and maintain model quality through clear processes and governance. Analytics Product also shapes the future of the Analytics & Investor Platform by defining the multi‑year strategy for analytics and investor workflows, building leading private markets and whole‑portfolio analytics capabilities, shaping analytics infrastructure to support the next phase of growth, and delivering Open Analytics and APIs to enable Open Aladdin. The team is motivated by commercial outcomes and industry leadership, powered by exceptional talent and deep subject‑matter expertise, accelerated by a strong embrace of AI technologies, and committed to launching exciting careers. About Performance & Attribution: The Performance & Attribution team within Analytics Product (AP) delivers Aladdin’s performance and return analytics to support better portfolio decisions and differentiate investment solutions. Partnering across investment, client, analytics, data and technology teams to deploy new architecture, models and solutions across a wide range of asset classes and client segments. Our team is known for: Problem solving: We partner with investment, risk and client-facing teams to understand their business problems and provide creative solutions using Aladdin analytics. Innovation: We sit at the intersection of finance and technology. We conceptualize, build and implement new capabilities so Aladdin remains the best platform for clients to understand and manage portfolios and risk. Centralized & scalable operating platform: Aladdin is a global investment platform that helps us solve problems in a scalable and efficient manner. About the role: We are looking for a new member in the AP Performance & Attribution Team to help support the ever-increasing demand for Aladdin’s performance measurement and performance attribution capabilities. Portfolio performance evaluation involves performance measurement, performance attribution and performance appraisal. Performance attribution plays a key role in the investment process. It provides feedback throughout portfolio management and explains investment decisions to clients. It helps investors understand the key drivers of active return: Sector Allocation decisions or ability to research attractive investment opportunities at the individual asset level. This team plays a coordinating role in defining product strategy, conceptualizing, designing, testing, and deploying new capabilities, working closely with financial modelers, engineers, product managers and users. You will also work with clients and relationship managers to ensure that clients are getting the most out of Aladdin’s performance capabilities and that client feedback is addressed appropriately. We offer a dynamic, team-oriented environment with tremendous learning and growth potential. Overview of Responsibility: Collaborate with Modeling and Research, Quantitative Technology, and Aladdin Product Management to analyze, create specifications for and test enhancements to performance measurement and attribution calculators and presentation capabilities. Work closely with Quantitative Tec ... (truncated, view full listing at source)
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