Credit Risk Quant

ERM Placement Services

Dadri

On-site

INR 2,600,000 - 5,800,000

Full time

9 days ago
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Job summary

ERM Placement Services in Mumbai seeks a Manager-Credit Risk Quant with 6 to 8 years of experience to lead analytics engagements, model development/validation, and advisory work in Basel/IFRS 9 contexts.

Responsibilities include leading client engagements, mentoring teams, and delivering high-impact risk solutions while collaborating with senior stakeholders to drive business outcomes.

Qualifications

  • Strong expertise in credit risk analytics and regulatory compliance.
  • Proficient in PD/LGD/EAD/ECL methodologies.
  • Knowledge of Basel Accords and IFRS 9 (ECL).
  • Experience in Enterprise Risk Management and risk governance.
  • Exposure to credit policy, scoring models, and regulatory requirements.
  • Proficiency in Python or R for quantitative analysis.
  • Excellent communication and stakeholder management.
  • Experience leading client engagements and teams.

Responsibilities

  • Lead credit risk consulting engagements for Banks, NBFCs, and financial institutions.
  • Develop, review, and validate credit risk models (PD, LGD, EAD, ECL).
  • Advise on credit risk management, regulatory compliance, and ERM initiatives.
  • Interpret and implement Basel II/III and IFRS 9 regulations.
  • Assess and enhance credit policies, underwriting, governance, and scoring.
  • Collaborate with clients to capture requirements and design solutions.
  • Present findings to CXO-level stakeholders and clients.
  • Mentor project teams and drive timely delivery of engagements.
  • Support business development with proposals and client relationships.

Skills

Credit risk analytics
Regulatory frameworks
Quantitative risk modeling
Leadership
Client-facing communication
Python
R
Stakeholder management
Presentation skills

Job description

Manager-Credit Risk Quant

Location: Mumbai

Experience: 6 to 8 Years


About the Role

We are looking for an experienced Manager Credit Risk Quant to join our Financial Risk & Regulations practice. The ideal candidate will possess strong expertise in credit risk analytics, regulatory frameworks, and quantitative risk modeling, with experience across banking and financial services. This is a client-facing role requiring leadership capabilities, strategic thinking, and the ability to deliver high-impact risk solutions.


Key Responsibilities

  • Lead credit risk consulting and analytics engagements for Banks, NBFCs, and other financial institutions.
  • Develop, review, and validate credit risk models, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), Expected Credit Loss (ECL), and portfolio pooling methodologies.
  • Provide advisory on credit risk management, regulatory compliance, and enterprise risk management initiatives.
  • Interpret and implement regulatory frameworks such as Basel Accords and IFRS 9 (ECL).
  • Assess and enhance credit policies, underwriting processes, risk governance, and credit rating/scoring methodologies.
  • Collaborate with clients to understand business requirements and design effective risk management solutions.
  • Present recommendations and insights to senior stakeholders, including CXO-level executives.
  • Lead project teams, mentor team members, and ensure timely delivery of high-quality client engagements.
  • Contribute to business development by supporting proposals, identifying growth opportunities, and building strong client relationships.

Required Skills & Experience

  • Strong understanding of wholesale, retail, and alternative lending products, including Microfinance.
  • Hands-on experience in credit risk model development and/or validation covering PD, LGD, EAD, ECL, and related methodologies.
  • In-depth knowledge of Basel Accords, IFRS 9 (Expected Credit Loss), and credit risk regulatory requirements.
  • Experience in Enterprise Risk Management (ERM) and credit risk governance.
  • Exposure to credit policy, credit processes, risk scoring, rating models, and regulatory compliance.
  • Proficiency in quantitative analysis using R or Python is preferred.
  • Excellent analytical, problem-solving, and stakeholder management skills.
  • Strong communication and presentation skills with experience engaging senior leadership and clients.

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