About the job
We are seeking a highly skilled and motivated Vice President to join our Credit Quantitative Trading (QT) team, within the JPMorgan Quantitative Trading and Research (QTR) umbrella. This is a unique opportunity to work with Credit asset class, specifically in corporate bonds, bond portfolios, and fixed income ETFs globally. You will be involved in comprehensive analytics, models, and tools used in various trading activities within High-Touch and Low-Touch (Algo/Systematic) bond market making.
Responsibilities
Investing in existing AI/ML models and continuously improving capabilities to keep up with modern frameworks
Collaborate with market makers, traders, and other stakeholders to support trading activities and strategies.
Analyze market trends and large datasets, translating them into actionable insights using various methodologies relevant to the projects.
Design and implement tools and systems end-to-end, ensuring that models and analytics comply with industry best practices.
Foster a deep understanding of how different parts of the business connect and contribute to the overall success of both the individual and the team.
Drive projects with a keen eye from a quantitative research perspective, ensuring they progress in the right direction for long-term success.
Qualifications
Minimum
A post-graduate degree in a STEM discipline (e.g., Mathematics, Physics, Engineering, Computer Science) with hands-on experience in AI/ML timeseries models and traditional statistical modeling.
Minimum 3 to 5 years of experience in a quantitative research or related role within e-trading space
Strong knowledge of corporate credit, fixed income markets, and ETFs.
Excellent analytical skills with a keen attention to detail and a systematic approach to problem-solving, with a willingness to explore new ideas.
Ability to work collaboratively in a fast-paced, dynamic environment, while also demonstrating independent thinking and exceptional organizational capabilities.
Strong communication skills to effectively convey complex concepts to non-technical stakeholders.
Preferred
Expertise in deep learning, time series modeling, with the ability to experiment with and apply various modeling techniques to enhance predictive accuracy and insights.
Advanced proficiency in programming languages such as Python and Java, enabling the development and implementation in libraries, micro-services, and systems.