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For Companies At a Glance
- Tasks: Join our team to develop cutting-edge financial models and tools for diverse asset classes.
- Company: BlackRock is a global leader in investment management, dedicated to financial well-being.
- Benefits: Enjoy flexible time off, education reimbursement, and comprehensive health resources.
- Why this job: Be part of a collaborative culture that values innovation and personal growth.
- Qualifications: PhD/Master in relevant fields with 5+ years in quantitative modeling required.
- Other info: Hybrid work model allows for both in-office collaboration and remote flexibility.
The predicted salary is between 57600 - 84000 £ per year.
The Modeling and Research team 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 models and tools across many different areas - single-security pricing, prepayment models, risk, return attribution, liquidity, optimization and portfolio construction, scenario analysis and simulations, etc. and 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. Modeling and Research also conducts leading research on the areas above, delivering state-of-the-art models. They also publish applied scientific research frequently, and our members present regularly at leading industry conferences. Modeling and Research engages constantly with the sales team in client visits and meetings.
Key Responsibilities:
The Modeling and Research team is looking for multiple quantitative researchers in various fields of expertise for roles across our teams. The researchers' primary job responsibilities are to develop methodologies, models, and analytics to help portfolio and risk managers to better conduct valuation or manage risks and rewards at both security and portfolio level. We are specifically hiring for the following teams.
The Portfolio Simulation Research team
This team specifically is building out a new engine for the joint simulation of the global macro economy, drivers of financial markets, and individual assets. The team is building and connecting innovative models and methodologies across these spaces in a Bayesian framework. The engine is used in scenario analysis and portfolio construction / strategic asset allocation.
Responsibilities for this team include:
- Doing theoretical research to come up with new, or find existing models and methodologies in the risk space, across multiple asset classes including private assets
- Doing empirical research to calibrate new models to financial data
- Backtesting, documenting, and guiding new models and methodologies through validation
- Communicate with internal and external clients to identify industry-wide quantitative problems and collaborate with academics affiliated with BlackRock to explore solutions
- Collaborate on papers for publication, presenting original research at industry conferences, and speaking with institutional clients about relevant research.
Additional job responsibilities may include working with portfolio management teams on bespoke projects supporting their investment processes or working with financial advisory teams on modeling projects for bespoke products.
For the simulation team, the requirements are:
- PhD/Master in Finance, Statistics/Econometrics, Economics or other relevant quantitative disciplines
- A minimum of 5+ years' experience in quantitative modeling and analytics. Experience in people management is a plus but not required
- Experience in private market modeling / private cashflow modeling is a plus
- Demonstrated ability to conduct high quality empirical research or theoretical research relevant for empirical analysis.
- Knowledge of financial mathematics (derivatives pricing).
- Experience with Bayesian or experience with machine learning
- Able to communicate quantitative information and collaborate effectively in a team environment
- Able to communicate with internal stakeholders and external clients
- Solid programming skills in Python and a drive and ability to quickly pick up new technologies.
- Exposure to Git, Unix, SQL, or any high-performance computing language is a plus but not required.
- Exposure to PyTorch/Jax is a plus but not required
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.
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.
Quantitative Modeling, Vice President employer: BlackRock, Inc.
Contact Detail:
BlackRock, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Modeling, Vice President
✨Tip Number 1
Familiarise yourself with the latest trends in quantitative finance and modelling. Stay updated on recent publications and research in the field, especially those related to Bayesian methods and machine learning, as these are key areas for the role.
✨Tip Number 2
Network with professionals in the industry, particularly those who work at BlackRock or similar firms. Attend relevant conferences and seminars where you can meet potential colleagues and learn more about the specific challenges they face in quantitative modelling.
✨Tip Number 3
Brush up on your programming skills, particularly in Python, as well as any exposure to Git, SQL, or high-performance computing languages. Consider working on personal projects or contributing to open-source projects to demonstrate your coding abilities.
✨Tip Number 4
Prepare to discuss your past research experiences and how they relate to the responsibilities of the role. Be ready to explain your methodologies and findings clearly, as communication is crucial when collaborating with internal and external clients.
We think you need these skills to ace Quantitative Modeling, Vice President
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative modeling and analytics. Emphasise any specific projects or roles that align with the responsibilities outlined in the job description, particularly those involving empirical research or financial mathematics.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background in finance, statistics, or econometrics makes you a suitable candidate. Mention any experience with Bayesian methods or machine learning, as these are key aspects of the position.
Showcase Your Research Skills: If you have published research or presented at conferences, be sure to include this in your application. Highlight any theoretical or empirical research you've conducted that is relevant to the role, especially in the context of risk management or portfolio construction.
Demonstrate Communication Skills: Since the role involves collaboration with internal and external clients, provide examples in your application of how you've effectively communicated complex quantitative information in previous roles. This could include teamwork experiences or client interactions.
How to prepare for a job interview at BlackRock, Inc.
✨Showcase Your Quantitative Skills
Make sure to highlight your experience in quantitative modeling and analytics. Be prepared to discuss specific projects where you've developed methodologies or models, especially those related to financial data and risk management.
✨Demonstrate Your Research Abilities
Since the role involves both theoretical and empirical research, come ready to talk about your past research experiences. Discuss any published papers or presentations at industry conferences, as this will show your commitment to advancing knowledge in the field.
✨Communicate Effectively
This position requires collaboration with internal and external clients. Practice explaining complex quantitative concepts in simple terms, as well as discussing how you’ve successfully communicated findings to stakeholders in the past.
✨Familiarise Yourself with Relevant Technologies
Brush up on your programming skills, particularly in Python, and be ready to discuss any experience you have with tools like Git, SQL, or machine learning frameworks. Showing that you can quickly adapt to new technologies will be a plus.
