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JPMorgan Modeling Analyst 
India, Karnataka, Bengaluru 
130635218

22.09.2024

Job Responsibilities:

  • Evaluate, test, and validate vendor models for their effectiveness to address the business proposition being evaluated (typically credit risk) as well as other risk components.
  • Understand/evaluate efficiency of state-of-the-art modeling techniques including both classical statistical modeling approaches and modern machine learning approaches to enhance existing models and tackle challenging modeling problems.
  • Manage end-to-end model development process, including data sourcing, manipulation, exploratory data analysis and pattern discovery, documentation, assisting with implementation, and performance monitoring.
  • Collaborate with cross functional partners in Risk, Finance, Technology, Model Governance throughout the entire modeling life cycle.
  • Interact with third party vendors and making sure Chase can gain maximum synergies on use of these vendor models.

Required qualifications, capabilities, and skills

  • Advanced degree in a quantitative discipline (e.g., Mathematics, Statistics, Economics, Computer Science, Operations Research) with minimum 6 years of relevant working experience
  • Strong data analysis and statistical/economic modeling experience, such as generalized linear models, multivariate analysis, and time series analysis.
  • Proficiency in advanced analytical languages (e.g., SAS, Python, R)
  • Ability to work with large data and perform extensive analysis to draw useful insights.
  • Strong communication skills to present to and collaborate with business partners and model end-users.
  • Strong organizational and multi-tasking skills with demonstrated ability to manage expectations and deliver quality results on time.
  • Comfortable working both independently and in a team environment.

Preferred qualifications, capabilities, and skills

  • Knowledge of vendor management/ similar experience in past is very useful
  • Familiarity with framework of machine learning pipeline (e.g., tensor flow, scikit-learn) is not required but a plus.