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Quantitative Trading & Research - Markets Capital - Vice President

Job in City of Rochester, Rochester, Monroe County, New York, 14602, USA
Listing for: JPMorgan Chase & Co.
Full Time position
Listed on 2026-06-02
Job specializations:
  • IT/Tech
    Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: City of Rochester

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

Job Summary

As Vice President in the Quantitative Trading & Research (QTR) team, you will deliver on AI and data-driven solutions as well as complex challenges related to the management and reporting of risks, pnls 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 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 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 AI and 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 AI platforms, fostering a culture of continuous improvement.
  • Build and maintain strong relationships with global Quantitative Trading & Research (QTR) teams, driving global collaboration.
Required qualifications, capabilities, and skills
  • Experience with in a quantitative role in finance
  • Hold a degree in a quantitative discipline such as Mathematics, Computer Science, Physics, Engineering or AI
  • 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.
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