Clearing Risk Analyst

Analyze clearing-member positions, collateral, settlement obligations, and concentrations, investigating significant changes and exceptions and recommending follow-up actions.

Contribute to the development and review of margin methodology by analyzing collateral coverage, stress scenarios, and backtesting results, and pressure-testing the underlying assumptions.

Assess risks tied to new products, business changes, and market events by identifying potential failure scenarios and developing recommendations for the DCO risk lead.

Build and refine risk reporting and recurring monitoring, validating figures against source records, defining clear metrics, distinguishing missing or stale data from a genuine absence of exposure, and streamlining workflows for efficiency.

Partner with Product, Operations, Finance, Legal, and Compliance to evaluate how funding, settlement, and processing failures create financial risk across the trade lifecycle, and help draft and maintain related risk procedures and control documentation.

Prepare concise risk analyses, incident reviews, and management materials that clearly separate confirmed facts, assumptions, open questions, and recommendations.

1 to 3 years of experience in market risk, counterparty risk, derivatives clearing, or trading operations at a major financial institution, exchange, or clearinghouse.

Working knowledge of derivatives products and margin models, including how trades create positions, funding needs, and settlement obligations, and how initial and variation margin protect against counterparty exposure.

Familiarity with clearing risk concepts such as stress and backtesting, collateral management, or settlement exception analysis.

Demonstrated ability to take an open-ended risk question, structure a work plan, source the right data, and deliver a considered recommendation with minimal direction.

Sound judgment on escalation — knowing when an issue requires deeper investigation versus immediate action, and communicating limitations clearly.

Comfort working with spreadsheets and data, including checking calculations, investigating inconsistencies, and communicating conclusions that are clearly traceable to evidence.

Responsible use of generative AI, maintaining human oversight to validate outputs, deliver business-ready results, and drive measurable improvements in workflow efficiency, cost, and quality.