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Associate, Market Risk Manager

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Onsite

Associate, Market Risk Manager

Cantor Fitzgerald

Associate, Market Risk Manager

Skills

SQL QueriesPythonRData AnalysisMachine LearningAINLP / Natural Language ProcessingRisk Management

2 months ago

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Important information


Contract type:

Permanent

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

19 August 2026

What they need


📍 New York,

💼 2-5 Years Experience

💰 Competitive + Bonus

Role Overview

We are seeking a Market Risk Manager to enhance our existing risk management framework and process. This role sits at the intersection of quantitative finance and applied artificial intelligence, requiring expertise in both domains. You will partner closely with trading desks, technology, and senior leadership to embed AI-driven insights directly into our risk management structure.

Key Responsibilities

Risk Monitoring & Reporting

  • Work as part of the market risk team to produce daily, weekly, and monthly risk reporting across equities, rates, structured fixed income, credit, FX, and commodities, incorporating AI to enhance their content and production.
  • Develop and enhance risk measures such as VaR, Stress Loss, and Expected Shortfall across the firm’s trading activities.
  • Define, implement, and monitor flags and limits and escalate as appropriate.
  • Present risk insights to trading management with clarity, leveraging AI-assisted visualization and commentary tools.

Risk Framework & AI Integration

  • Work to embed AI and machine learning models in the firm’s risk process to enhance stress testing, VaR, and other risk measurement methodologies.
  • Lead the transition from legacy rule-based risk monitoring to adaptive, AI-powered surveillance systems capable of handling non-linear exposures, risks arising from complex structured products, and tail risks.

Required Qualifications

  • 2-5 years in market risk management at a bank, asset manager, or hedge fund
  • CFA, FRM, or PRM designation preferred
  • Bachelor’s degree in Finance, Mathematics, Statistics, Physics, or Engineering
  • Advanced degree in a quantitative discipline
  • Deep expertise in risk metrics: VaR, Expected Shortfall, Greeks, scenario/stress analysis, Monte Carlo simulation methodologies
  • Experience with LLMs or NLP applied to financial data
  • Hands-on experience and expertise in Microsoft Excel, SQL, Bloomberg analytics and API
  • Coding experience in VBA, R, and Python; experience with MSCI RiskMetrics

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