VP - Wholesale Portfolio Analytics - Grading

JPMorgan Chase JPMorgan Chase · Banking · Mumbai, Maharashtra, India · Corporate Sector

This role focuses on developing and maintaining credit risk grading models and frameworks for Wholesale Credit Risk clients. It involves quantitative work, methodology design, data pipeline development using Python, and applying LLMs to synthesize unstructured data for model development. The role also requires translating analytical findings for senior leadership and regulators, and partnering with technology and control teams.

What you'd actually do

  1. Lead the development of credit risk grading models and frameworks for the Wholesale Credit Risk organization. This means hands on quantitative work, strategic thinking about methodology and regular exposure to senior leadership.
  2. Own the end-to-end development and enhancement of risk grading frameworks, from methodology design through implementation and validation
  3. Build and maintain python based pipelines for managing large credit datasets, running back tests, and producing portfolio level analytics that stress test model assumptions
  4. Apply LLMs to synthesize unstructured data (financials, research, news) into datasets for use in development
  5. Translate complex analytical findings into clear narratives for senior committees and regulators

Skills

Required

  • 7+ years in financial analytics or Credit Risk
  • Strong python skills with hands-on experience manipulating large datasets (pandas, SQL, Numpy) and building reproducible tools and analytical workflows
  • Proven ability to build or enhance quantitative models – back testing, sensitivity analysis, scenario modeling
  • Experience producing executive-level communications: decks memos, committee materials
  • Comfortable presenting to senior audiences and defending analytical conclusion
  • Familiarity with credit risk concepts: PD, LGD

What the JD emphasized

  • quantitative work
  • methodology design
  • Apply LLMs

Other signals

  • Develop and maintain risk grading models and methodologies
  • Build and maintain python based pipelines for managing large credit datasets
  • Apply LLMs to synthesize unstructured data