At a Glance
- Tasks: Manage risk and generate returns using cutting-edge AI solutions in quantitative trading.
- Company: WorldQuant, a leader in systematic financial strategies and innovative technology.
- Benefits: Competitive salary, performance bonuses, and comprehensive benefits package.
- Other info: Join a culture that values creativity, collaboration, and continuous improvement.
- Why this job: Combine portfolio management with advanced AI to make impactful financial decisions.
- Qualifications: Advanced degree in a quantitative field and familiarity with financial markets.
The predicted salary is between 108000 - 180000 £ per year.
WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
We are seeking a Portfolio Manager to manage risk and generate returns while utilizing cutting-edge agentic AI solutions within our Quantitative Trading divisions. This role sits at the intersection of Portfolio Management and Artificial Intelligence, requiring active engagement with autonomous cognitive systems for strategy development.
As a Portfolio Manager focused on Agentic Systems, you will manage a live trading book while working with cognitive reasoning architectures that enable autonomous systems to solve complex financial problems and reason through multi-step solutions. You will utilize and interact with agentic systems including planning algorithms, memory architectures, reflection mechanisms, and collaborative reasoning patterns that support autonomous decision-making in quantitative trading environments. You will adjust hyperparameters of reinforcement learning training processes to optimize system performance and contribute to deep learning model development for the PM model layer and custom agentic workflows.
Responsibilities
- Portfolio Management: Take risk, manage P&L, and make trading decisions within defined risk parameters while developing expertise in quantitative portfolio management principles.
- Agentic Systems Utilization: Deploy and work with cognitive reasoning systems for quantitative modeling problems, leveraging planning, tool use, memory, reflection, and collaboration capabilities.
- Reinforcement Learning Tuning: Adjust hyperparameters of reinforcement learning training processes to improve autonomous system performance and decision-making quality.
- Model Development: Contribute to deep learning model building for PM model layer applications specific to portfolio management objectives.
- Custom Agentic Development: Build and customize agentic workflows and tools tailored to portfolio management needs and specific trading strategies.
- Human-in-the-Loop Oversight: Execute human-in-the-loop decisions and checks ensuring that traded strategies meet quant trading acceptance criteria.
This position combines portfolio management with cutting-edge agentic AI technology. Your work will directly impact:
- Research-to-production cycles for quantitative strategies.
- Complex, multi-step financial workflows through autonomous systems.
- Enhanced decision-making through human-AI collaboration.
What You’ll Bring
- Advanced degree in a quantitative field (Computer Science, Mathematics, Physics, Statistics, Engineering, or related discipline).
- Minimum of 10 years of experience; PM experience is not required but preferred.
- Familiarity with financial markets.
- Experience with python-based deep learning model development.
- Willingness to learn portfolio management discipline, including P&L responsibility and risk management.
- Hands-on experience with agentic AI frameworks.
- Deep knowledge of the core capabilities of agentic systems: planning, tool use, memory, reflection, and collaboration.
- Experience applying reinforcement learning methodologies to develop autonomous systems that learn and improve through policy optimization, reward modeling, and outcome-based feedback loops.
- Ability to adjust hyperparameters and tune training processes for reinforcement learning systems.
WorldQuant is a total compensation organization where you will be eligible for a base salary, discretionary performance bonus, and benefits. To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on job function and level, benchmarked against similar stage organizations. When finalizing an offer, we will take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package. The Base Pay Range For This Position Is 150,000 USD.
At WorldQuant, we are committed to providing candidates with all necessary information in compliance with pay transparency laws. If you believe any required details are missing from this job posting, please notify us at [email protected], and we will address your concerns promptly.
By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy explains how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction.
WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.
Portfolio Manager, Agentic Systems employer: WorldQuant
WorldQuant is an exceptional employer that fosters a culture of innovation and collaboration, where employees are encouraged to challenge conventional thinking and contribute to cutting-edge financial strategies. With a focus on continuous improvement and intellectual growth, team members have access to advanced resources and training opportunities, ensuring they thrive in their roles. Located in a dynamic environment, WorldQuant offers competitive compensation packages and a commitment to diversity, making it an attractive place for talented individuals seeking meaningful careers in finance and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Portfolio Manager, Agentic Systems
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your experience with agentic systems and quantitative trading. Use real examples to demonstrate how you've tackled complex problems and made decisions that led to successful outcomes.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of reinforcement learning and portfolio management principles. Be ready to discuss how you would apply these concepts in real-world scenarios, especially in relation to the role at WorldQuant.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at WorldQuant.
We think you need these skills to ace Portfolio Manager, Agentic Systems
Some tips for your application 🫡
Show Off Your Skills:When you're writing your application, make sure to highlight your quantitative skills and any experience with AI systems. We want to see how you can bring your unique talents to the table!
Tailor Your Application:Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Portfolio Manager role. We love seeing candidates who understand what we’re all about.
Be Clear and Concise:Keep your writing clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and how it relates to the role. No need for fluff!
Apply Through Our Website:Make sure to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!
How to prepare for a job interview at WorldQuant
✨Know Your Numbers
As a Portfolio Manager, you'll need to demonstrate your understanding of quantitative principles. Brush up on key metrics and financial models relevant to portfolio management. Be ready to discuss how you would apply these in real-world scenarios, especially when it comes to managing risk and generating returns.
✨Showcase Your AI Savvy
Since this role involves working with agentic AI solutions, make sure you can talk about your experience with AI frameworks and reinforcement learning. Prepare examples of how you've used these technologies in past projects, and be ready to discuss how they can enhance decision-making in trading environments.
✨Prepare for Problem-Solving Questions
Expect to face complex, multi-step problems during the interview. Practice articulating your thought process clearly as you work through these challenges. Highlight your ability to think critically and collaborate with AI systems to arrive at effective solutions.
✨Cultural Fit Matters
WorldQuant values a culture of open thinking and continuous improvement. Be prepared to discuss how you challenge conventional thinking and contribute to a collaborative environment. Share examples of how you've fostered innovation in your previous roles, as this will resonate well with their ethos.
