Role Focus :
- Identify potential problems, build the hypothesis, identify research data attributes and determine approach to solve analytical problems specifically in the area regulatory risk and modeling
- Understand, extract, clean and prepare the data for analysis
- Build complex programs for running statistical tests on data and for understanding correlation of various attributes. Perform detail exploratory data analysis on the data and report findings
- Compare and weigh numerical model outputs (preferably from SAS) and identify best choice models
- Build challenger models, build and validate models and ensure models with good predictive power as well as those which meet regulatory and audit standards.
- Make recommendations for procedural improvements supported by analytical findings
- Build presentations for targeted audiences
- Pragmatic approach to deliver fit to purpose strategies for bank under clear timelines.
Skill Requirement :
- Experience in Statistical Modeling with techniques like Linear Regression, Logistic Regression, Decision Trees within the gamut of scorecard development.
- Working knowledge of aspects like PD, LGD, EAD, impairment calculations, macroeconomic modeling, SICR, representativeness, back-testing will be given higher preference.
- Understanding of collections and recoveries tools such as Debt-manager etc. will be an advantage.
- Mandatory experience in SAS, Python or R
- Strong communication skills
Candidate profile:
- Master's in Business Administration or Masters in Statistics or Economics or Operational Research or Masters/Bachelors in Engineering
- Prior experience working with a bank or a banking analytics team under a 3rd part consultancy.
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