JPMorgan Quantitative Research - Credit Vice President 

United States, New York, New York 

710319094

In addition to traditional quantitative methods, the team is keen to explore and integrate various AI/ML methodologies into our modeling approach. This involves a scientific exploration of innovative techniques, with a focus on developing and deploying proven results in a production setting end-to-end. You need to be a forward-thinking individual who can bridge the gap between cutting-edge research and practical application, ensuring that AI/ML models are robust, scalable, and aligned with business objectives.

Job Responsibilities:

• Develop and enhance quantitative models and analytics for corporate bonds, bond portfolios, and fixed income ETFs.
• 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.

Required Qualifications, Capabilities, and Skills:

• A post-graduate degree in a STEM discipline (e.g., Mathematics, Physics, Engineering, Computer Science) with hands on experience in statistical modeling, .
• Minimum 3 to 5 years of experience in a quantitative research or related role within the financial industry.
• 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 Qualifications, Capabilities, and Skills:

• Expertise in time series data 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, or Java, enabling the development and implementation in libraries, micro-services, and systems.