Financial Engineering, Associate
BlackRockBU3-Budapest-GTC White House, Vaci ut 47, District XIII, BudapestPosted 2 April 2026
Job Description
About this role
Are you interested in building innovative technology that shapes global financial markets? Are you motivated by solving complex, quantitative problems in a
fast paced , collaborative environment? Do you want to work alongside experienced technologists and financial engineering experts to deliver
mission critical
solutions at scale?
BlackRock is recruit ing
multiple
f ina ncial
e ngineering professionals in Budapest
across s everal teams within
Aladdin Financial Engineering (AFE) . These roles span a range of quantitative and engineering disciplines and offer the opportunity to contribute to the development of the Aladdin platform across diverse business areas .
The teams we are hiring to are :
Model Governance Team
Single Security Pricing Team
Performance Attribution Team
Private Markets SWAT Team
While the specific responsibilities vary by team, all posit ions
focus on building robust, scalable technology and quantitative models that support investment
decision
making , risk management, and regulatory requirements for BlackRock and its global client
base.
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 range 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.
We are:
Passionate about building high quality
models
to meet the needs of tomorrow
Delivering solutions for both BlackRock investment users and over 100 global financial firms
Developing in
C ,
Python
or
other
programming
languages, with
cutting edge
technologies
A team who loves to innovate and continuously deliver value to our users through
quantitative solutions
You are:
Passionate about
quantitative solutions
with personal ownership for the work you do
Curious and eager to learn new things, with a healthy disrespect for the status quo
Love working within a successful team, learning
from
and helping others
Willing to embrace work outside your comfort zone, and push boundaries
Data and quality focused, with an eye for the details that make great solutions
You sometimes make mistakes, but always learn from them
Requirements:
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
2 years
of
relevant working experience
Strong programming skills and experience using Python or
C
to conduct statistical/econometric analyses
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
An ability to translate
real business
problems into technical solutions
Ability and willingness to learn fast, multi-task, self-motivate and pick up new things easily.
Ability to work independently and efficiently in a fast-paced and team-oriented environment.
Demonstrated ability to build positive relationships.
Good to have:
Knowledge of Private Markets and/or Performance
Attribution modelling
background is a plus
Knowledg ... (truncated, view full listing at source)
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