Quantitative Developer, Associate

About this role

About Quantitative Analytics Engineering

BlackRock is one of the world’s preeminent asset management firms and an outstanding provider of global investment management, risk management, and advisory services to institutional, intermediary and individual investors around the world. Besides offering a range of investment solutions — from fundamental and quantitative active management approaches to highly efficient indexing strategies – BlackRock also provides direct access to its market leading analytic models by onboarding clients to its Aladdin Platform, an end-to-end portfolio management software solution.

The Investments and Trading Engineering (ITE) team builds and delivers Aladdin's industry-leading risk management, portfolio management, compliance and trading capabilities. Within ITE, Quantitative Analytics Engineering (QAE) is a global team of quantitative developers responsible for the implementation of security valuation, portfolio risk, liquidity and performance attribution models. BlackRock Portfolio managers and external Aladdin clients such as pension funds and insurance companies rely on models maintained by QAE to identify investment opportunities, build portfolios and manage risk.

About the role

Join us as a senior C++ Developer in QAE Budapest to craft the next generation of our single security analytical modelling engine using C++ 20 and Python 3 with the help of colleagues across Europe and USA!

Take part in improving analytical systems by replacing existing functions with new implementations and craft a more scalable and modular architecture.

You will create new modules, APIs and build new applications to provide clients with novel ways of using our analytics.

You will communicate with the users of our analytical systems and with stakeholders formulating external client requirements.
You will also approach other teams in BlackRock to learn about the business use-cases we serve and how they could be recreated more efficiently on the new platform.

We work in an integrated, agile team with a focus on quality of work validated through automated testing, and we value effective and clean code.

Our analytical models are the heart of BlackRock, having them delivered in a scalable and reliable way is a cross-team effort valued by all the parties involved.

About our team

Security Analytics Infrastructure (SAI) is an established team of QAE with presence in Budapest, New York, and Zurich with most of the people in Budapest.

We develop scalable, high throughput, low latency analytical software for valuation of fixed income products like swaps or bonds, and of derivatives.

Challenging the status quo is our norm, and we excel in building modern systems and onboarding innovative technology like microservice architectures. We are pioneers of the firm and early adopters of new tools and industry standards. We are a diverse team with different ideas working towards the same goal.

Our dominant programming languages are C++ and Python.

We are passionate about what we do and hope you are, too!

Requirements

You should be

• Experienced in enterprise software development (2-4 years)
• Eager to work as part of a software development team
• Pragmatic and solution oriented
• Ready to learn new things

You are familiar with

• C++14 or later. At least 1 year’s work experience with C++.
• Design patterns
• Python or a scripting language (bash, PowerShell)
• Software development tools (test frameworks, version control, debugging)
• Continuous Integration

Nice to know

• C++ development tools (CMake, CLion)
• Google Protocol Buffers
• Unix systems (Red Hat, Ubuntu)
• Profiling tools (gprof, valgrind, gperftools)
• DevOps tools (Azure DevOps)

Knowledge of finance and fixed income asset types is a plus but not a must. We will help to learn what is needed.

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 reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.  Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

BlackRock is proud to be an Equal Opportunity Employer.  We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.