As an associate within the Modeling Centre of Excellence team, you will be responsible in developing quantitative methodologies to support the activities of the global Commercial & Investment Bank Planning & Analysis Group (with presence in New York, London and Mumbai), sitting out of Commercial & Investment Bank Research & Analytics in Mumbai.
The incumbent will be working in a team of roughly 35 individuals and be responsible for the design, engineering, industrialization and support of the CIB Quantitative Framework for the planning and forecast processes, ad hoc analysis for senior management and other strategic initiatives to support the businesses.
The team is based out of L&T office of J.P. Morgan in Powai, Mumbai.
Job Responsibilities:
- Perform in-depth data analysis, using statistical and machine learning modeling techniques (regression, decision tree, ECM, neural networks, regime switching, etc.), to creatively build predictive or explanatory models
- Devising/improving models on new/existing regression models. This includes coding the entire statistical methodology in R, Python
- Translate business needs into quantitative analyses and tools; communicate complex results to senior stakeholders in a clear and precise manner
- Work independently and collaboratively to establish close partnerships with peers across the greater CIB organization and Global Treasury.
- Develop metrics and statistical model prototypes that can be used to drive business decisions.
- Lead and participate in ad-hoc projects as needed by senior management or regulatory initiatives
- Clearly document the code of the tools created; Publish and maintain clear user documentation; Write the official Model documentation and interact with the Model Governance group for review and approval; Ensure full SIT / UAT and Change controls of tools
Required qualifications, skills & capabilities:
- Experience of working on R/Python statistical, analytical and machine learning libraries of 3-7 years
- Experience of working on probability theory, statistics and machine learning
- Close attention to detail and ability to work to very high standards
- Strong quantitative and analytical skills
- Strong communication skills (both written and verbal) and ability to present findings to a non-technical audience
- Ideal candidates for these positions would be graduates/post-graduates with good academic records from esteemed universities with exposure to finance/actuaries/accounting & derivatives
- Strong knowledge of Banking, Equities, FX, Rates, Fixed Income or Commodities