Credit Portfolio Lending Group - Quantitative Research - Associate or Vice President

JPMorgan Chase & Co.; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

JPMorgan Chase & Co. seeks an Associate or Vice President in Quantitative Research for the Credit Portfolio Lending Group (CPG). You will design, build, and deploy AI-driven tools to support trading workflows, risk monitoring, and portfolio optimization.

You will collaborate with global teams, leverage machine learning and LLM methodologies, and contribute to automation across CPG. A strong foundation in quantitative methods and Python is essential for success.

Qualifications

• Advanced degree in mathematics, statistics, physics, financial engineering, computer science, or equivalent.
• Experience in quantitative research, markets, or analytics supporting fixed income, credit, or lending desks.
• Hands-on experience building and deploying AI agents, machine learning, or LLM-based applications for financial markets or trading workflows.
• Experience in portfolio optimization and familiarity with related software and tools.
• Strong software design and data science skills, with Python experience.
• Exceptional analytical, quantitative, and problem-solving skills, with intellectual curiosity and passion for credit markets.
• Excellent written and verbal communication skills, able to convey complex quantitative concepts to technical and non-technical stakeholders.
• Ability to work in a high-pressure, collaborative team environment with strong attention to detail and quality.

Responsibilities

• Design, build, and deploy AI, LLM, and generative AI agent-based tools for CPG trading workflows.
• Explore and implement machine learning techniques to enhance trading-signal generation and portfolio optimization.
• Stay at the forefront of emerging AI capabilities and identify practical applications for daily desk operations.
• Leverage credit portfolio data to identify opportunities, concentrated exposures, and optimal hedging strategies.
• Collaborate with model control teams for timely review and approval of models, ensuring compliance.
• Automate daily risk and position reports, streamlining workflows for broader automation and digital transformation.
• Build and enhance trade support and automation infrastructure for portfolio hedging, credit curve reconciliation, and loan sale execution.
• Interact with other Markets QR sub-teams to explore synergies and share best practices.

Skills

Quantitative research

Python

Machine learning

Portfolio optimization

Financial engineering

Communication skills

Education

Advanced degree in mathematics or related field

Tools

Python libraries (NumPy/Pandas)

Modeling frameworks

Job description

Join our team to build your career in a culture that values innovation, creativity, and excellence. As an Associate or Vice President in Quantitative Research for the Credit Portfolio Lending Group (CPG), you will be at the forefront of developing and deploying AI-driven solutions that transform portfolio management and trading. You’ll collaborate with global teams, leverage advanced technologies, and drive automation to accelerate decision-making and optimize credit risk strategies. This is your opportunity to make a meaningful impact, grow your expertise, and contribute to a dynamic, global function.

As an Associate or Vice President in Quantitative Research within CPG, you will design, build, and deploy AI, LLM, and generative AI agent-based tools to support trading workflows, market analysis, and portfolio risk monitoring. You’ll explore machine learning techniques to enhance trading-signal generation, optimize portfolios, and automate daily risk and position reports. You’ll collaborate with model control teams, leverage data to identify opportunities and hedging strategies, and interact with other Markets QR sub-teams to share best practices. Your role will be central to advancing automation and digital transformation across CPG.

Job responsibilities

• Design, build, and deploy AI, LLM, and generative AI agent-based tools for CPG trading workflows.
• Explore and implement machine learning techniques to enhance trading-signal generation and portfolio optimization.
• Stay at the forefront of emerging AI capabilities and identify practical applications for daily desk operations.
• Leverage credit portfolio data to identify opportunities, concentrated exposures, and optimal hedging strategies.
• Collaborate with model control teams for timely review and approval of models, ensuring compliance.
• Automate daily risk and position reports, streamlining workflows for broader automation and digital transformation.
• Build and enhance trade support and automation infrastructure for portfolio hedging, credit curve reconciliation, and loan sale execution.
• Interact with other Markets QR sub-teams to explore synergies and share best practices.

Required qualifications, capabilities, and skills

• Advanced degree in mathematics, statistics, physics, financial engineering, computer science, or equivalent.
• Experience in quantitative research, markets, or analytics supporting fixed income, credit, or lending desks.
• Hands-on experience building and deploying AI agents, machine learning, or LLM-based applications for financial markets or trading workflows.
• Experience in portfolio optimization and familiarity with related software and tools.
• Strong software design and data science skills, with Python experience.
• Exceptional analytical, quantitative, and problem-solving skills, with intellectual curiosity and passion for credit markets.
• Excellent written and verbal communication skills, able to convey complex quantitative concepts to technical and non-technical stakeholders.
• Ability to work in a high-pressure, collaborative team environment with strong attention to detail and quality.

Preferred qualifications, capabilities, and skills

• Experience collaborating with global teams and sharing best practices.
• Experience automating trading desk workflows and risk reports.
• Experience with model control and compliance processes.
• Proactive approach to learning and professional development.
• Experience in credit portfolio management or trading.

This role encompasses the performance of UK regulated activity. The successful candidate will therefore be subject to meeting UK regulatory requirements in the assessment of fitness, propriety, knowledge and competence (as assessed by the Firm) and (where appropriate) approval by the UK Financial Conduct Authority and/or the Prudential Regulation Authority to carry out such activities.