Quantitative Strategist - Balance Sheet Strategy & Financial Resource Analysis, AVP

Position

Location: New York, NY (on site)

Employment Type: Full-Time

Position Overview

Mizuho is seeking a highly motivated Quantitative Strategist (AVP) to join the Balance Sheet Strategy (BSS) - Financial Resource Analysis team, a group at the center of the firm's efforts to measure, forecast, and optimize the consumption of regulatory capital and other scarce financial resources. As regulatory capital requirements grow in complexity-driven by Basel III Endgame, SA-CCR, and evolving market and counterparty risk standards-this role offers the opportunity to help build the analytical foundation that informs how Mizuho deploys its balance sheet.

The successful candidate will combine strong quantitative and programming skills with a solid understanding of U.S. regulatory capital frameworks to develop RWA analytics, capital forecasting tools, and balance sheet optimization capabilities across Counterparty Credit Risk (CCR), Securities Financing Transactions (SFT), Credit Valuation Adjustment (CVA), and Market Risk. Beyond producing metrics, the role is expected to generate actionable insights that shape business strategy, pricing, and capital allocation decisions.

A key dimension of the role is the practical application of AI and machine learning techniques-including generative AI and large language models-to enhance forecasting accuracy, automate analytical and documentation workflows, and accelerate the interpretation of complex regulatory rules. The Quantitative Strategist will operate at the intersection of quantitative finance, regulation, and technology, working closely with Treasury, Market Risk, Credit Risk, Finance, Technology, Model Validation, and senior management, with significant visibility across the organization.

Key Responsibilities

• Develop and enhance quantitative analytics for RWA, regulatory capital, leverage exposure, and financial resource optimization across CCR, SA-CCR, SFT, CVA, and Market Risk.
• Perform RWA attribution, forecasting, and capital consumption analyses to identify optimization opportunities.
• Support Basel III Endgame implementation, including rule interpretation, impact assessments, and parallel runs.
• Build and maintain Python-based models and data pipelines for capital forecasting, scenario analysis, and stress testing.
• Apply AI / Machine Learning techniques to enhance forecasting, pattern detection, data quality, and analytical accuracy.
• Leverage generative AI and Large Language Models (LLMs) to accelerate documentation, code development, rule interpretation, and process automation.
• Automate regulatory capital calculations and develop scalable analytics and reporting capabilities.
• Prepare methodology documentation and analytical specifications in line with model governance standards (SR 26-2).
• Support interactions with Model Validation, Internal Audit, Regulatory Reporting, and regulators.
• Present analytical findings and capital impacts to business and senior management stakeholders.

Qualifications & Skills

Education

• Bachelor's or master's degree in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Economics, Engineering, Computer Science, Data Science, or a related quantitative field.
• Professional certifications such as CFA, FRM, PRM, or CQF are a plus.

Experience

• 3 or more years of experience in regulatory capital, financial resource management, balance sheet management, or quantitative risk analytics at a large financial institution.
• Hands-on experience with one or more of: SA-CCR, CCR, SFT, BA-CVA, Market Risk Capital, or Basel III Endgame.
• Practical experience applying AI / machine learning or generative AI tools in a financial or analytical context is highly desirable.

Technical Skills

• Regulatory: Strong knowledge of Basel III / U.S. Basel III Endgame, SA-CCR, CCR, SFT, BA-CVA, Market Risk Capital, and RWA methodologies.
• Quantitative: Model development, statistical analysis, forecasting, and exposure measurement; solid understanding of derivatives and securities financing.
• AI & Machine Learning: Familiarity with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch), generative AI / LLMs, and their application to analytics, automation, and productivity. Awareness of AI governance and model risk considerations.
• Technology: Advanced Python and SQL; Pandas / NumPy and Power BI. Databricks, PySpark, Snowflake, Azure, and Git preferred.

Soft Skills

• Strong analytical and problem-solving abilities.
• Clear communication of technical concepts to non-technical audiences.
• Intellectual curiosity and eagerness to adopt emerging AI-driven tools and techniques.
• Detail-oriented, self-motivated, and able to manage multiple priorities in a fast-paced, regulated environment.

Other requirements

Mizuho has in place a hybrid working program, with varying opportunities for remote work depending on the nature of the role, needs of your department, as well as local laws and regulatory obligations. Roles in some of our departments have greater in-office requirements that will be communicated to you as part of the recruitment process.