Performance & Attribution , Quantitative Modeler, Vice President
BlackRockBU3-Budapest-GTC White House, Vaci ut 47, District XIII, BudapestPosted 2 April 2026
Job Description
About this role
About Aladdin Financial Engineering (AFE):
Join a diverse and collaborative team of over 400 modelers and technologists in Aladdin Financial Engineering (AFE), the business responsible for the research and development of Aladdin’s financial models. This group is also accountable for analytics production, enhancing the infrastructure platform and delivering analytics content to portfolio and risk management professionals (both within BlackRock and across the Aladdin client community). The models developed and supported by AFE span a wide array of financial products covering equities, fixed income, commodities, derivatives, and private markets. AFE provides investment insights that range from an analysis of cash flows on a single bond, to the overall financial risk associated with an entire portfolio, balance sheet, or enterprise.
Role Description:
The Modelling Research team in AFE is looking for a performance attribution modeller to join the Budapest team to contribute to the modelling and development effort in building and maintaining of Aladdin performance attribution models. The new member should help to support the increasing demand for Aladdin’s performance measurement and performance attribution capabilities
mainly focusing
on
enhanc ing
capabilities for private
market
analytics, multi-asset portfolio
modeling ,
and improve attribution accuracy for illiquid assets.
Portfolio performance evaluation involves performance measurement, performance attribution and performance appraisal. Performance attribution plays a key role in the investment process, both as a feedback loop in the investment process as well as providing a means of articulating the implication of investment decisions to clients
This team is responsible for the design and support of performance attribution models including documentation, testing, performance monitoring and other model governance exercises working closely with colleagues in
product analytics , 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.
Key Responsibilities:
The candidate will be performing duties related to all aspects of performance attribution model development:
Researching, designing new performance attribution models
Collaborating with software developers to test and release new models into production
Supporting existing performance attribution models in production; developing and improving model quality control and model performance monitoring; maintaining and extending research framework
Investigating and resolving client queries relating to model methodology and functionality
Key Skills & Qualifications
Graduate degree in a technical field (Maths, Statistics, Computer Science and/or Engineering, Finance, Econometrics, Physics)
Postgraduate degree in a technical field is a plus
6 years relevant working experience
Knowledge of Private Markets and Performance
Attribution
modelling
Strong programming skills and experience using Python to conduct statistical/econometric analyses
Knowledge in Unix/Linux, Git is a plus
Strong knowledge of financial, mathematical, and statistical theory
Strong oral and written (English language) communication skills that enable complex ideas to be readily understood by team members and clients
Enthusiasm, flexibility, and maturity to adapt to the needs of a dynamic group and deliver within strict time frame
Good time management skills including the ability to handle multiple projects
Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education ... (truncated, view full listing at source)
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