At a Glance
- Tasks: Develop and implement quantitative tools to enhance trading performance in London.
- Company: Join a leading investment firm with a focus on innovation and analytics.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborate with senior traders and drive high-impact projects in a fast-paced setting.
- Why this job: Make a real impact in trading by leveraging AI and quantitative analysis.
- Qualifications: 7-12 years in quantitative finance with strong programming skills, especially in Python.
The predicted salary is between 100000 - 150000 £ per year.
We are seeking a Principal to join Apollo’s PM & Trading Strats team within Global Corporate Credit (GCC), based in London. GCC Strats sits inside the business and serves as the technical and quantitative resource for PM and Trading. In this role, you will work directly with senior traders and business leadership to identify opportunities, develop ideas, and drive execution on tools, analytics, and workflows that improve decision‑making, risk management, execution, and investment performance. This role will be primarily focused on the London trading business, covering Corporate Bonds, CDS, Loans, Equities, and Macro trading.
We are looking for someone highly analytical, technically strong, and commercially minded – someone who can engage credibly with senior stakeholders, present ideas clearly, take ownership, and get high‑impact work over the line. The candidate requires strong judgment, a bias toward action, and the ability to turn real desk problems into scalable tools and actionable analytics. As artificial intelligence reshapes investment workflows, this person will help identify and drive high impact use cases across trading into production, including bringing research content such as analyst views and issuer intelligence more directly into day‑to‑day decision making.
The mandate of PM & Trading Strats is to contribute to investment performance by building the analytics, tools, and automation used by Traders and PMs across Global Corporate Credit. PM & Trading Strats turns Apollo’s market data, internal portfolio context, research content, and other investment inputs into actionable, real‑time outputs that improve pricing and execution decisions, strengthen risk management, and systematically surface the best opportunities across markets. The team also develops portfolio construction and decision tools that help PMs allocate capital, integrate new deal flow, and manage liquidity more deliberately through stronger start‑of‑day views, ranked adds/trims/switches, and automated flagging of drift, inefficiencies, and risk issues. The mandate includes laying the foundation for scalable systematic capabilities across the business and connecting research, data, and analytics more directly to day‑to‑day investment decision making. This role reports directly to the COO of the business and also into the firm’s core Quant team, helping align business priorities with consistent quantitative excellence, technical discipline, and scalable execution across the Credit platform.
Primary Responsibilities
- Build and own quantitative tools & analytics that support alpha generation for London Trading, while coordinating closely with peers in NY to ensure alignment across the broader platform.
- Drive end‑to‑end delivery of desk critical tools, working directly with traders and business leadership to identify opportunities, source data, design models or logic, and lead implementation, rollout, and iteration.
- Lead alpha research and signal development by structuring datasets, running backtests and analysis, pressure testing assumptions, and translating outputs into scalable tools and monitoring.
- Partner with Engineering and Data to improve the reliability and scalability of Strats tooling, including data pipelines, APIs, compute, monitoring, and documentation.
- Help build out systematic capabilities across the London trading business, supporting signal‑to‑trade workflows and more scalable decision making across Corporate Bonds, CDS, Loans, Equities, and Rates, in alignment with the broader GCC Strats agenda.
- Apply quantitative analysis to day‑to‑day desk questions, including pricing and relative value, liquidity, risk, positioning, and what changed/why diagnostics, while turning recurring needs into reusable tools over time.
- Implement AI‑enabled workflows across trading, working with Strats, COO, Engineering, and the business to move high‑impact use cases into production, including areas such as research integration, summarization, and workflow automation.
Qualifications & Experience
- 7–12 years of experience in quantitative finance, strats, trading analytics, systematic research, risk analytics, or a comparable role on the buy side or sell side.
- Strong markets judgment and relevant product knowledge across some combination of corporate credit, CDS, loans, equities, and rates.
- Strong programming skills, with Python required, and a track record of building real tools used by investment teams, including analytics, dashboards, screens, alerts, and data pipelines. C++ or Java is a plus.
- Solid foundation in statistics, applied math, and modeling, with practical experience working with large and varied datasets including market data, issuer level data, positions, exposures, and liquidity measures.
- Proven ability to operate in a high touch environment with traders and senior stakeholders, with strong communication skills, clear ownership, and sound prioritization instincts.
- Experience identifying high value opportunities, presenting ideas clearly, and driving execution from concept through delivery.
- Exposure to AI and ML is a plus, especially LLM enabled workflows such as retrieval, search, extraction, summarization, and evaluation, but the core requirement is delivering scalable tooling that improves investment decision making.
- Degree in quantitative discipline such as Mathematics, Statistics, Physics, Engineering, Computer Science, or a similar field. Advanced degree preferred but not required with strong relevant experience.
Principal - Quant Trading employer: Apollo Global Management, Inc.
Apollo is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets finance. With a strong focus on employee growth, we provide opportunities for professional development and collaboration with senior traders and business leaders, ensuring that your contributions directly impact investment performance. Our culture fosters creativity and analytical thinking, making it an ideal place for those looking to thrive in quantitative finance while leveraging cutting-edge technology like AI to enhance decision-making processes.
Contact Details:
Apollo Global Management, Inc. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Principal - Quant Trading
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and trading sectors. Attend industry events, webinars, or even casual meet-ups. The more people you know, the better your chances of hearing about opportunities before they hit the job boards.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative tools and analytics projects. Whether it's a GitHub repository or a personal website, having tangible examples of your work can really impress potential employers and set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Research the company and its trading strategies thoroughly. Be ready to discuss how your experience aligns with their needs, especially in areas like AI integration and risk management. Confidence and knowledge go a long way!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might not be listed elsewhere. Plus, applying directly shows your enthusiasm and commitment to joining our team. Let’s get you that dream job!
We think you need these skills to ace Principal - Quant Trading
Some tips for your application 🫡
Show Your Analytical Skills:Make sure to highlight your analytical prowess in your application. We want to see how you've tackled complex problems in the past, especially in quantitative finance or trading analytics. Use specific examples to demonstrate your ability to turn data into actionable insights.
Tailor Your Application:Don’t just send a generic CV and cover letter! Tailor your application to reflect the skills and experiences that align with the role. We’re looking for someone who can engage with senior stakeholders, so make sure to showcase your communication skills and relevant experience.
Highlight Technical Proficiency:Since this role requires strong programming skills, particularly in Python, be sure to mention any relevant projects or tools you've built. We love seeing real-world applications of your technical abilities, so don’t hold back on sharing your achievements!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at Apollo Global Management, Inc.
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative finance knowledge. Be ready to discuss your experience with tools and analytics you've built, especially in Python. They’ll want to see how you can apply your skills to real-world trading scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems in trading or analytics. Think about specific instances where you turned desk issues into scalable solutions. This will demonstrate your ability to think critically and act decisively.
✨Engage with Stakeholders
Since this role involves working closely with traders and senior leadership, practice articulating your ideas clearly. Be ready to explain how your work has impacted decision-making and risk management in previous roles.
✨Stay Ahead of AI Trends
Familiarise yourself with the latest trends in AI and machine learning, especially as they relate to trading workflows. Be prepared to discuss how you can leverage these technologies to enhance investment decision-making and improve efficiency.