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Portfolio Risk Modeling - Associate

Posted Yesterday
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In-Office
New York, NY
133K-162K Annually
Internship
In-Office
New York, NY
133K-162K Annually
Internship
The Associate will develop and test portfolio risk models, support existing models, and resolve client queries related to model functionality. Responsibilities include research, collaboration with developers, and enhancing model quality control.
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About this role

Aladdin Financial Engineering – New York (Portfolio Risk Modelling team Associate)

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, development, and adoption 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.

The Portfolio Risk team builds and maintains multiple 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 cover a wide variety of fixed income, equity, and alternatives asset classes. The models utilize sophisticated econometric/statistical methods and tools.  Aladdin model suite is utilized by traders, portfolio managers and risk managers at BlackRock and platform’s clients, and influence investment activity.  We strive to lead and implement models that scale with our growing Analytics’ business ensuring adherence to BlackRock’s rigorous standards of model governance.

AFE is looking for a quantitative researcher to contribute to the development of BlackRock’s proprietary fixed income portfolio risk models and associated risk methodologies. These models are used in portfolio risk management, performance attribution, and portfolio construction for all portfolios running through Aladdin’s platform.

Job Responsibilities

  • The candidate will be performing duties related to all aspects of portfolio risk model development:
  • Researching, designing, and back-testing new risk models using Python infrastructure
  • Collaborating with software developers to test and release new models into production
  • Supporting existing risk models in production; developing and improving model quality control and model back-testing procedures; maintaining and extending research framework
  • Investigating and resolving client queries relating to model methodology and functionality

Key Skills & Qualifications

  • MFE degree with Internship or a PHD in a technical field (Econometrics, Finance, Maths, Statistics, Computer Science and/or Engineering)
  • Hands-on experience dealing with large and complex data sets and leveraging econometric/statistical techniques to conduct high quality empirical research.
  • Strong programming skills and experience using Python/R to conduct statistical/econometric analyses
  • Experience with various ML/AI algorithms is a plus.
  • Knowledge in Unix/Linux, Git is a plus
  • Strong knowledge of financial, mathematical, and statistical theory
  • Strong interest in financial market
  • 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
  • Interest in portfolio risk modelling
For New York, NY Only the salary range for this position is USD$132,500.00 - USD$162,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.

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.

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 workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.

 

BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email [email protected]. All requests are treated in line with our privacy policy.

BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.

Top Skills

Python,R,Risk Modeling,Unix/Linux,Git,Machine Learning,Econometrics,Statistical Methods

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