Quantitative Research (QR) is an expert quantitative modelling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modelling and portfolio management. As a global team, QR partners with traders, marketers and risk managers across all products and regions.

Job summary:

As an Associate in the Quantitative Research (QR) team, you will deliver on data-driven solutions and complex challenges related to the management and reporting of liquidity, funding, and capital. You will lead the team in designing and implementing advanced models to assess risk, as well as developing tools to predict and explain P&L. You will work closely with the Markets Treasury team as well as our technology partners.

This position offers exposure to large-scale data analytics, the application of AI, automation of reporting processes, and the creation of actionable insights for senior management and cross-functional teams. You will collaborate with stakeholders across markets and technology to drive innovative solutions. This role provides a unique opportunity to enhance treasury management practices and support strategic objectives in a fast-paced, evolving market environment.

Job Responsibilities: 

• Architect and oversee the design of advanced frameworks for complex data analytics ensuring scalability, security, and maintainability.

• Lead sophisticated data analysis initiatives, deriving insights from large and diverse financial datasets to inform strategic decision-making and drive business outcomes.

• Design, implement, and manage end-to-end analytics solutions and user tools, setting standards for best practices and maximizing value delivered to stakeholders

• Engage with leadership and business teams to proactively identify opportunities for optimizing financial resource allocation and quantify the impact of proposed initiatives.

• Establish and nurture partnerships with technology teams to drive the development and scaling of innovative analytical frameworks and optimization strategies, influencing the firm’s technology roadmap.

• Lead the automation strategy by identifying and transforming complex manual processes into efficient, scalable digital platforms, fostering a culture of continuous improvement.

• Build and maintain strong relationships with global Quantitative Research (QR) teams, driving global collaboration.

Required qualifications, capabilities, and skills: 

• Experience within a quantitative role in finance

• Hold an advanced degree (Master’s) or equivalent in a quantitative discipline such as Mathematics, Computer Science, Physics, or Engineering

• Demonstrate expert-level programming skills, particularly in Python, with experience leading development of large-scale, production-grade systems and mentoring others in best coding practices.

• Exhibit exceptional quantitative and analytical problem-solving abilities

• Markets experience and a comprehensive understanding of trading concepts, strategies, and terminology

• Possess outstanding communication skills, adept at engaging and influencing senior stakeholders on complex technical topics and translating technical concepts into actionable business insights.

• Demonstrate ability to master new business domains and adapting to evolving business priorities, proactively identifying areas for strategic growth and improvement.

• Apply strategic and creative thinking to both challenges and opportunities, driving continuous innovation and fostering a culture of forward-thinking problem solving.

• Champion robust system and solution architecture, ensuring rigorous testing, verification, and adherence to best practices in design and implementation across teams.

Preferred qualifications, capabilities, and skills:

• Demonstrate deep expertise in derivatives pricing theory and financial regulations, with a history of applying this knowledge to drive strategic initiatives and influence firm-wide practices.

• Possess a comprehensive understanding of bank balance sheet management and extensive experience solving complex financial optimization problems, contributing to strategic decision-making and resource allocation.

• Champion rigorous tes