Credit Portfolio Group - Quantitative Research - Associate

JOB DESCRIPTION

The Credit Portfolio Lending Group (CPG) is a public-side global function with approximately 25 Portfolio Management and Trading professionals across New York, London, and Singapore, and is part of the Markets function within the Commercial & Investment Bank (CIB). CPG has two primary functions: Portfolio Management & Research (PM&R), which is aligned by industry and geography, and Trading & Distribution (T&D), which uses both liquid and illiquid channels to risk manage the book. The priority of the group is to manage the retained credit portfolio, focusing on concentrated exposures (company-specific, industry, or geographical concentrations) while balancing the competing priorities of minimizing cost, P&L volatility, and capital usage. Portfolio Managers and Researchers work with Traders to determine appropriate strategies to manage the portfolio, achieved primarily via the secondary loan market, the CDS market, and through structured solutions.

The Quantitative Research (QR) function supporting CPG is responsible for developing and maintaining models for valuation, risk, and P&L calculations, as well as building analytics, portfolio monitoring tools and algorithms that support CPG's activities. Responsibilities span the full lifecycle from new model specification and approval through to implementation in libraries and integration into risk and P&L systems.

Job Summary

We are seeking a diligent, quantitative, self-motivated, and outgoing individual to join the Credit Portfolio Group in New York in a Quantitative Research capacity. In this role, you will serve as the primary quant for CPG delivering cutting-edge tools and models that enhance the group's portfolio management, trading, and distribution capabilities. There will be a particular emphasis on leveraging AI, large language models (LLMs), and generative AI agents to design and implement market-based tools that provide the desk with a quantitative edge, accelerate automation, and improve decision-making across the credit portfolio.

Job Responsibilities

Design, build, and deploy AI, LLM, and generative AI agent-based tools to support CPG trading workflows, including automated market analysis, credit curve maintenance, trade idea generation, and portfolio risk monitoring

Explore and implement machine learning techniques to enhance market-making algorithms, quoting tools, and portfolio optimization strategies

Stay at the forefront of emerging AI capabilities and identify practical applications that can be embedded into the desk's daily operations

Leverage the vast amount of data available across the credit portfolio to proactively identify opportunities, concentrated exposures, and optimal hedging strategies for the desk

Collaborate with model control teams to facilitate timely and efficient review and approval of all models, ensuring compliance with internal policies and industry regulations

Automate trading desk daily risk and position reports, streamlining workflows to accelerate the broader automation & digital transformation agenda across CPG

Build and enhance trade support and automation infrastructure for portfolio hedging strategies, credit curve reconciliation, and loan sale execution

Interact with other sub-teams within Markets QR to explore synergies and share best practices

Required Qualifications, Capabilities, and Skills

An advanced degree in mathematics, statistics, physics, financial engineering, computer science, or an equivalent subject

At least 4 years of experience in a quantitative research, markets, or analytics-focused role supporting a fixed income, credit, or lending desk

Hands-on experience building and deploying AI agents, machine learning or LLM based applications, with demonstrated ability to apply these technologies to financial markets or trading desk workflows.

Hands-on experience in portfolio optimization, familiar with related software and tools

Strong software design and data science skills, with Python experience

Exceptional analytical, quantitative, and problem-solving skills with an intellectual curiosity and passion for credit markets and investing.

Excellent written and verbal communication skills, with the ability to convey complex quantitative concepts to both technical and non-technical stakeholders.

Ability to work in a high-pressure, collaborative team environment with strong attention to detail and a focus on quality of deliverables

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

ABOUT THE TEAM

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.