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Front Office Quant Risk Analyst, Global Credit Fund, New York - JMD Reg Consultancy LTD

JMD Reg Consultancy LTDNew York, NY🇺🇸United StatesPosted 31 Aug 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to develop advanced quantitative skills and contribute to a leading global credit fund, leveraging AI/ML techniques in risk analysis. You'll thrive here if you possess a strong STEM background, a solid understanding of quantitative credit risk, and a passion for financial statement analysis. Apply now to join a dynamic team and make a significant impact on investment strategies.

Quick Overview

Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
New York, NY, United States
Posted
2 weeks ago
Microsoft OfficeUnderwriting

Job Description

Our client is a leading global, credit-focused alternative investment manager providing creative capital solutions and attractive risk-adjusted returns across the capital structure. The firm is known for combining intellectual rigor with the scale to serve companies of all sizes through standard and customized solutions.

The Role

We are looking for an Analyst/Associate to join the Front Office Quant team within the firm's Global Quant Group.

Responsibilities

  1. Build, maintain and apply models for ratings analytics and quantitative credit risk measurement (PD and LGD)
  2. Maintain and enhance risk scorecards and dashboards across the firm's investment strategies
  3. Liaise with deal teams to track and audit the use of quant credit models in loan underwriting and ongoing portfolio monitoring
  4. Develop and enhance early-warning system, risk, and relative-value models and workflows across public and private credit
  5. Apply AI/ML techniques to quant credit workflows
  6. Perform fundamental analysis of financial statements to support early identification of credit events, fraud-risk triage and data quality assurance

Qualifications

  1. Strong academic background in a STEM field
  2. 1–5 years' experience in a quantitative team
  3. Solid grounding in statistics and quantitative credit risk concepts
  4. Strong understanding of financial statements and basic accounting
  5. Advanced Microsoft Office and SQL skills; familiarity with Python
  6. Excellent communication, presentation and analytical problem-solving skills
  7. Highly organized, detail-oriented, and able to work autonomously

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