Why Mizuho Mizuho

Why Mizuho Mizuho

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

New York, NY (1271 AOA/6th Ave) · Full-time

Sponsorship not specified$91k-$145kDetected 7 days ago
PythonGitSQLSnowflakeDatabricksAzureMachine LearningTensorFlowPyTorchscikit-learnPandasNumPyData EngineeringData ScienceLLMsStatisticsForecastingValuationM&AAuditingCommunicationProblem SolvingInternal AuditCFA

About the role

  • Beyond producing metrics, the role is expected to generate actionable insights that shape business strategy, pricing, and capital allocation decisions.
  • Awareness of AI governance and model risk considerations. - Technology: Advanced Python and SQL; Pandas / NumPy and Power BI.
  • The expected base salary ranges from $91,000 - $145,000.

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.
  • Automate regulatory capital calculations and develop scalable analytics and reporting capabilities.
  • Support interactions with Model Validation, Internal Audit, Regulatory Reporting, and regulators.
  • Detail-oriented, self-motivated, and able to manage multiple priorities in a fast-paced, regulated environment.
  • Gain senior management exposure and drive data-driven balance sheet strategy.

Requirements

  • Strong knowledge of Basel III / U.S. Basel III Endgame, SA-CCR, CCR, SFT, BA-CVA, Market Risk Capital, and RWA methodologies.
  • Familiarity with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch), generative AI / LLMs, and their application to analytics, automation, and productivity.
  • Hands-on experience with one or more of: SA-CCR, CCR, SFT, BA-CVA, Market Risk Capital, or Basel III Endgame.

Nice to have

  • Leverage generative AI and Large Language Models (LLMs) to accelerate documentation, code development, rule interpretation, and process automation.
  • Prepare methodology documentation and analytical specifications in line with model governance standards (SR 26-2).
  • Present analytical findings and capital impacts to business and senior management stakeholders.
  • 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.
  • 5-8 years of experience in regulatory capital, financial resource management, balance sheet management, or quantitative risk analytics at a large financial institution.

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.
  • 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.
  • Why Join Us?
  • Shape Mizuho's Financial Resource Analysis and regulatory capital capabilities.
  • Contribute to major initiatives including Basel III Endgame implementation.

Compensation

  • The expected base salary ranges from $91,000 - $145,000.

Benefits

  • Help pioneer the adoption of AI and machine learning in regulatory capital analytics.
  • Competitive compensation, comprehensive benefits, and performance-based incentives.
  • Apply AI / Machine Learning techniques to enhance forecasting, pattern detection, data quality, and analytical accuracy.
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