VP- Economic Capital Modelling

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This role leads a portfolio of quantitative credit risk initiatives spanning Economic Capital (EC) modeling, production and simulation and wholesale credit model development (PD/LGD/EAD, rating, loss, stress testing)

The Senior Manager is accountable for end-to-end delivery: defining the roadmap and project scope, establishing timelines and governance, managing resources, and ensuring high-quality, well-controlled model and process outcomes.

The position requires frequent engagement with Credit Administration, Model Risk/Governance, and (as applicable) regulators, translating business needs into scalable quantitative solutions and production-grade processes.

This role also manages and develops a team of quantitative professionals across multiple concurrent projects and supports global alignment and standardization of methodologies.

Key Accountabilities & Responsibilities

1) Quantitative Project & Portfolio Management (Managerial Ownership)

• Define and manage a portfolio of quantitative projects (models, frameworks, production processes, tooling), including business case, scope, milestones, resourcing, risk/issue management, and delivery timelines.
• Establish project governance: steering updates, dependency tracking, stakeholder communications, and delivery sign-offs; ensure projects can run simultaneously with clear priorities and outcomes.
• Implement disciplined execution practices (e.g., agile/waterfall as appropriate), including documentation standards, testing plans, and production readiness checklists. (Senior enhancement)

2) Economic Capital Modeling & Production Leadership

• Oversee and continuously improve the global/regional EC production process, ensuring reliable monthly execution and controlled change management.
• Lead Monte Carlo simulation approaches for Economic Capital and tail loss estimation, including development of internal EC models and oversight of vendor solutions (e.g., Moody’s RiskFrontier).
• Drive standardization and alignment of EC modeling parameters across regions (e.g., systematic risk specification, PD/LGD correlation treatment), balancing methodological rigor and business usability.
• Enhance automation and resiliency of the production pipeline through modern engineering practices and tooling.

3) Credit Rating and Loss Model Development, Maintenance, and Methodology

• Lead development and ongoing maintenance of credit rating, credit loss, and stress testing models, ensuring robust performance and appropriate use.
• Own the design and evolution of PD/LGD/EAD frameworks (Basel-related model components) and extend models to be more agile and consistent with market and regulatory expectations.
• Apply advanced quantitative techniques (e.g., regression, multivariate methods, machine learning/deep learning where appropriate) within a controlled model lifecycle.
• Translate model outputs into high-impact insights and executive-ready materials for senior leadership.

4) Credit Loss Forecasting & Stress Loss Analytics

• Lead stress credit loss forecasting under prescribed macroeconomic scenarios and ensure consistent implementation across portfolios.
• Oversee implementation and updates of proprietary credit risk models supporting forecasting, monitoring, and scenario analysis (PD/LGD/EAD and related components).
• Ensure data lineage, reasonableness, and explainability for forecast drivers and results; institutionalize monitoring and recalibration triggers.

5) Model Governance, Audit, and Regulatory Readiness

• Lead interactions with model governance / model risk management teams to define performance metrics, monitoring standards, and acceptable operating ranges; resolve model issues promptly.
• Ensure models and processes meet internal audit and model management committee expectations through strong documentation, testing evidence, and transparent controls.
• Prepare and lead model reviews, respond to challenges, and implement remediation plans within agreed timelines.

6) Data, Technology, and Production Engineering

• Oversee extraction, standardization, and quality control of loan/portfolio data from multiple systems to enable portfolio modeling.
• Champion production-grade coding practices: peer code review, version control, automation, and reproducibility.
• Drive adoption of modern tools (Python/R; data frameworks such as Pandas; Git/Bitbucket; cloud such as AWS) to improve scale, speed, and reliability.

7) Stakeholder Management & Communication

• Work across a global organization with diverse stakeholders—often with conflicting priorities—to align requirements, communicate trade-offs, and deliver outcomes.
• Lead and facilitate dialogue with business partners on key risk measurement issues, including presentations and executive communications.
• Develop tools and materials that improve stakeholder communication and transparency.

8) People Leadership & Talent Development

• Lead and develop a team of quantitative analysts supporting multiple projects concurrently; provide coaching, performance management, and career development.
• Set team standards for model craftsmanship, documentation, and engineering quality; build succession and subject matter depth.
• Mentor junior staff to achieve their potential and career goals; foster a culture of accountability and continuous improvement.

Job Requirements:

Required Skillset List

A) Quantitative & Risk Domain Expertise

• Economic Capital concepts and simulation-based loss modeling (Monte Carlo), including vendor platform oversight (e.g., RiskFrontier).
• Credit model development: rating models, credit loss models, stress testing; PD/LGD/EAD frameworks.
• Strong statistical modeling toolkit (regression, multivariate analysis; ability to apply ML responsibly in a governed environment).

B) Model Governance & Controls

• Model performance monitoring design, thresholding, remediation planning, and governance engagement; ability to resolve model issues quickly.
• Strong documentation discipline, audit readiness, and committee/management communication.
• Ability to set governance standards across a function and drive consistent adoption.

C) Data & Engineering / Technology

• Advanced data analytics with large datasets; strong hands-on capability in Python and/or R (and SAS where relevant), including Pandas.
• Version control and collaborative development practices (e.g., Git/Bitbucket), peer reviews, and best coding practices.
• Familiarity with cloud computing (e.g., AWS) and ability to modernize/automate production processes.
• Strong production mindset: automation, testing, CI/CD concepts, and operational resilience for recurring processes.

D) Leadership, Project Management & Delivery

• Ability to define, plan, and manage quantitative projects end-to-end, including scope, milestones, resource planning, and stakeholder alignment.
• Proven capability to run multiple concurrent initiatives and prioritize effectively.
• Team leadership: hiring/mentoring, coaching, motivating, and developing junior talent.

E) Communication & Stakeholder Management

• Excellent written/oral communication and interpersonal skills; ability to present complex model results to senior management and facilitate dialogue with business partners.
• Ability to collaborate across regions and functions and manage competing priorities constructively.

F) Personal Effectiveness

• Strong critical thinking, problem-solving, organization, and attention to detail; ability to work independently with limited day-to-day supervision.

Preferred / Differentiating Qualifications

• Experience leading global standardization initiatives across regions and establishing common modeling/production standards.
• Experience supporting or partnering with Front Office and/or Credit Administration stakeholders in a major bank environment.
• Advanced degree (M.S./PhD) and/or professional certifications (e.g., FRM/CFA).

Education

• Bachelor’s degree required in a quantitative field (e.g., Statistics, Finance, Engineering, Computer Science).
• Advanced degree (Master’s/PhD) strongly preferred for this senior role.

Experience (Senior Manager expectation – intentionally above both source roles)

• 10+ years of progressive experience in credit risk analytics/modeling within banking/financial services (or equivalent).
• 3+ years managing quantitative professionals and delivering multi-workstream initiatives (direct people leadership + delivery accountability).
• Demonstrated experience with Basel-related models (PD/LGD/EAD) and model lifecycle management; stress testing experience strongly valued
• Proven delivery of productionized quantitative pipelines and/or recurring monthly processes; experience with EC production and Monte Carlo simulation preferred.

Mitsubishi UFJ Financial Group (MUFG) is an equal opportunity employer. We view our employees as our key assets as they are fundamental to our long-term growth and success. MUFG is committed to hiring based on merit and organsational fit, regardless of race, religion or gender.