
What you will be doing:
As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -
- Dive into the data and identify patterns
- Development of end-to-end Credit models and credit policy for our existing credit products
- Leverage alternate data to develop best-in-class underwriting models
- Working on Big Data to develop risk analytical solutions
- Development of Fraud models and fraud rule engine
- Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
- Working on cutting-edge techniques e.g. machine learning and deep learning models
Example of projects done in past:
- Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
- Fraud model development, deployment and rules for EMEA region
Basic Requirements:
- 1-3 years of work experience as a Data scientist (in Credit domain)
- 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
- Strong problem solving and understand and execute complex analysis
- Experience in at least one of the languages - R/Python/SAS and SQL
- Experience in in Credit industry (Fintech/bank)
- Familiarity with the best practices of Data Science
Add-on Skills :
- Experience in working with big data
- Solid coding practices
- Passion for building new tools/algorithms
- Experience in developing Machine Learning models

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