Wholesale Credit Risk - Counterparty Credit Risk (CCR) - Analyst

🏢 JP Morgan
📍 Ciudad Autónoma de Buenos Aires, ArgentinaFull-timeOn-site
📅 Posted: 2mo ago🔄 Updated: 2mo ago
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✨ AI Summary
The Counterparty Credit Risk (CCR) team within Wholesale Credit Risk is seeking an Analyst to evaluate, monitor, and mitigate counterparty credit risk. Responsibilities include analyzing exposures, designing stress testing scenarios, enhancing monitoring capacity with AI/LLM dashboards, and improving CCR metrics. The role involves supporting the consolidation of tactical tools into strategic solutions and producing regulatory/audit-ready documentation. Key requirements include a Bachelor's degree in a quantitative discipline, strong Python programming skills, and experience with AI/LLM-driven solutions. A solid understanding of derivatives, CCR concepts, and proficiency in Excel, Tableau, and Alteryx are necessary. Strong communication and risk judgment are also critical for this role.
Requirements
Requires a Bachelor's degree in a quantitative discipline, strong Python programming skills for analytics and automation, and experience designing/implementing AI/LLM solutions. Must have a good understanding of derivatives and CCR concepts, proficiency in Excel, and familiarity with visualization/ETL tools like Tableau and Alteryx. Strong communication and risk judgment are essential.
Description

Counterparty Credit Risk (CCR) team, part of Wholesale Credit Risk, is responsible for measuring counterparty exposures, conducting ad-hoc risk investigations and analyses in partnership with credit officers, assessing and negotiating CSA terms, determining initial margin requirements, and maintaining all credit exposure metrics. The team also leads regulatory and capital stress testing exercises (CCAR, EBA, ICAAP), monitors exposures at the JPM legal entity level, evaluates collateral pools for emerging risk themes, and provides credit coverage for clearing house counterparties, including regulatory advocacy.

 

As an Analyst in the Counterparty Credit Risk (CCR) Methodology team, you will be instrumental in evaluating, monitoring, and mitigating counterparty credit risk exposure. This role places a strong emphasis on developing methodologies, designing stress scenarios, and addressing analytical challenges within the risk infrastructure. This position requires a proactive team player with a curious mindset, a strong analytical foundation, and expertise in programming, AI/LLM, and data visualization tools.

Job Responsibilities

  • Analyze and monitor counterparty credit risk exposures using quantitative models and risk management frameworks.
  • Design, implement, and interpret stress testing scenarios to evaluate the impact of adverse market conditions on counterparty credit risk.
  • Conduct sensitivity analysis and scenario-based stress testing to identify potential vulnerabilities in credit portfolios.
  • Enhance CCR continuous monitoring capacity by delivering strategic tools to improve transparency, explainability, and governance of risk signals.
  • Design and implement AI/LLM-enabled dashboard capabilities to accelerate BAU monitoring, triage, and narrative generation while maintaining appropriate controls and auditability.
  • Increase comprehensiveness and accuracy of CCR metrics by reviewing and enhancing scenario coverage, validating methodology soundness, and performing unit/product back testing across relevant asset classes and products.
  • Leverage data to support scenario review and BAU analytics, translating findings into actionable methodology updates and governance materials.
  • Support the consolidation of tactical CCR tools into technology-owned strategic solutions, including requirements definition, control design, UAT, and production readiness.
  • Deliver regulatory-linked enhancements and control evidence
  • Produce regulator- and audit-ready documentation, testing evidence, and governance materials (assumptions, limitations, change management).

 

Required qualifications, capabilities, and skills

  • Bachelor’s degree in a quantitative discipline
  • Strong programming skills Python; ability to build repeatable analytics and automation with robust controls
  • Experience in designing and implementing AI/LLM-driven solutions (e.g., monitoring dashboards, workflow automation, narrative generation) in a controlled environment
  • Good understanding of derivatives (bilateral and cleared), Futures and Options, Margin Lending, and Securities Financing products
  • Solid grasp of CCR concepts: exposure measurement, PFE, wrong-way risk, sensitivities, stress testing, margin/collateral dynamics, and liquidity considerations
  • Proficiency with Excel; familiarity with visualization/ETL tools such as Tableau and Alteryx
  • Strong communication skills: able to translate technical methodology and analytics into clear governance-ready narratives for non-specialists
  • High ownership mindset and risk judgement: comfortable challenging assumptions, validating results, and driving issues to closure
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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00