Quantitative Modeler, Associate

About this role

About this role

BlackRock Overview

BlackRock is one of the world’s preeminent asset management firms and a premier provider of global investment management, risk management and advisory services to institutional, intermediary and individual investors around the world. BlackRock offers a range of solutions — from rigorous fundamental and quantitative active management approaches aimed at maximizing outperformance to highly efficient indexing strategies designed to gain broad exposure to the world’s capital markets. Our clients can access our investment solutions through a variety of product structures, including individual and institutional separate accounts, mutual funds and other pooled investment vehicles, and the industry-leading iShares® ETFs.

Aladdin Financial Engineering (AFE)

AFE is a diverse and global team with a keen interest and expertise in all things related to technology and financial analytics.  The group is responsible for the research and development of quantitative financial and behavioral models and tools across many different areas – single-security pricing, prepayment models, risk, return attribution, liquidity, optimization and portfolio construction, scenario analysis and simulations, covering all asset classes. The group is also responsible for the technology platform that delivers those models to our internal partners and external clients, and their integration with Aladdin.

AFE conducts leading research on the areas above, delivering state-of-the-art models. AFE publishes applied scientific research frequently, and our members present regularly at leading industry conferences. AFE engages constantly with the sales team in client visits and meetings.

Role

We are looking to hire a quantitative modeler to join our Portfolio Risk team.  This individual would have a strong background in quantitative research, have some experience with project management skills as well as proven experience of working in a team environment, collaborating with peer researchers and engineers, looking to also collaborate with team members in other regions. This person is expected to join as an individual contributor, leading research and development of model governance workstreams and gradually grow into an experienced researcher with expertise to represent and present our models and analytics to internal stakeholders and Aladdin clients.

The Portfolio Risk team builds a range of models and analytics including linear factor models, Value-at-Risk (VaR) methodologies, volatility and covariance matrix estimation and portfolio stress testing & scenario analytics. Our models use sophisticated econometric/ statistical methods and tools.  The models themselves have real practical value and are used by traders, portfolio managers and risk managers and influence investment activity. These models have a very large footprint of usage across the entire Aladdin client base, and so we place special emphasis on implementing models that scale with our growing Analytics’ business and ensuring adherence to BlackRock’s rigorous standards of model governance. This individual would be primarily focused on analytics project work related to streamlining the development of new portfolio risk models, expanding our model testing framework, and building a robust research platform, whilst working in conjunction with senior modelers in the global team.

You can...

• work at one of the world’s top FinTech companies. We sell our Aladdin analytics platform to over 100 of the top global financial institutions and corporations, handling many trillion USD of assets
• help develop and deploy quantitative financial models and portfolio analytics that are used to manage most of the money of the world’s largest asset manager
• bring all yourself to the job. From the top of the firm down we embrace the values, identities and ideas brought by our employees

Skills & Qualifications: 

• Research/Analytics professional with 3+ years of solid experience in quantitative/statistical modeling. Experience with market risk/factor models and portfolio risk analytics (VaR, Tracking Error, Stress Testing) is strongly preferred
• Undergraduate Actuary / Statistics / Applied Mathematics / Econometrics, advanced degree in quantitative discipline is a plus.
• Familiarity with financial products/risk management process is a strong plus.
• Exposure to model backtesting, quality controls, and validation is highly desirable 
• Hands-on experience with statistical software (e.g., Python, R, MATLAB) and strong background in programming, Python in particular, is a must
• Experience with large data set and various machine learning algorithms a plus 
• Prior work experience in financial modeling (e.g., risk models, analytics) or data science and model deployment to production environment is a strong plus

Competencies:

• Strong desire to apply quantitative skills to address financial problems and issues that BlackRock encounters in the course of business
• Strong analytical skills, attention to detail and strong work ethics
• Possesses a positive attitude and ability to work both independently and as part of a team (within a department or in an inter-departmental/virtual setting), in a fast-paced environment
• Possesses excellent communication and presentation skills
• Ability to synthesize requirements from multiple stakeholders and translate those into actionable plans
• Organized in carrying out the responsibilities, possess strong time management skills and should be high on focus

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents 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.

Guidance on AI use for candidates

At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.

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.

To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

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