Financial Engineering, Associate

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 recruiting multiple financial engineering professionals in Budapest across several 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 positions 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 

• Knowledge of Unix/Linux, Git is a plus 

• Stochastic calculus background