Counterparty Risk - Vice President

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Commercial & Investment Bank

Vice President role in Counterparty Risk at JPMorgan Chase, focusing on strengthening control frameworks, enhancing risk management processes, and driving transformation initiatives. Responsibilities include supporting risk controls, overseeing model compensating controls, monitoring portfolio thresholds, performing risk investigations, and driving projects. The role involves developing analytical tools using Python and potentially AI/LLM-enabled techniques, leveraging platforms like Tableau and Alteryx, and collaborating with various teams including Quantitative Research and Technology. Requires strong analytical skills, proficiency in Python and SQL, understanding of derivatives and CCR concepts, and excellent communication skills.

What you'd actually do

  1. Support and enhance the team’s risk control framework, including oversight of Risk Not In Stress (RNIS) and Risk Not In Peak (RNIP) and related control processes
  2. Oversee and challenge model compensating controls to ensure appropriate governance, monitoring and escalation of exposure-related adjustments
  3. Monitor and manage portfolio thresholds at an aggregate or portfolio level, investigate significant movements, and provide clear analysis and recommendations
  4. Perform ad hoc risk investigations and thematic analyses in response to market events, business questions, control reviews, or senior management requests
  5. Drive projects and transformation initiatives aimed at improving team efficiency, control robustness, data quality, and workflow effectiveness

Skills

Required

  • Bachelor’s degree in a discipline such as Financial Engineering, Mathematics, Physics, Statistics, Engineering, Finance and/or Economics
  • Strong analytical and problem-solving skills, with the ability to synthesize complex risk information, identify practical solutions, and communicate insights clearly to different audiences
  • Proficiency in Python programming and SQL, and experience using data and visualization tools such as Tableau, Alteryx, ThoughtSpot, or similar platforms to support analytics, automation, and process improvement
  • Good understanding of derivatives (bilateral and cleared), Futures and Options, Securities Financing, Prime Services, and related counterparty credit risk products
  • Understanding of key CCR concepts, including exposure measurement, PFE, collateral and margin, model overlays or compensation, portfolio thresholds, RNIS, RNIP, and stress or sensitivity analysis across asset classes
  • Proficiency with MS Excel and strong comfort working with large data sets and analytical workflows
  • Strong written and verbal communication skills, with the ability to explain technical concepts to non-specialists and engage constructively with a broad stakeholder group
  • Strong sense of accountability and ownership; self-motivated, control-minded, and confident in making, articulating, and challenging risk judgments where appropriate
  • Ability to work effectively across functions and build strong partnerships with Quantitative Research, Technology, Product, Credit Officers, and other stakeholders

Nice to have

  • Prior experience in market risk and/or counterparty risk, particularly in controls, analytics, portfolio management, collateral or exposure-related roles
  • Experience supporting risk control frameworks, governance processes, model-related controls, or portfolio threshold management
  • Experience delivering automation, reporting, or workflow improvement initiatives in a risk, analytics, or control environment, with the ability to translate business needs into practical solutions
  • Experience designing or implementing AI/LLM-enabled solutions to support analytics, automation, or workflow enhancement is advantageous
  • Familiarity with regulatory expectations, audit processes, and governance requirements relevant to counterparty credit risk is preferred
  • Experience working across diverse stakeholders in a complex global organization is advantageous

What the JD emphasized

  • AI/LLM-enabled techniques where relevant