- Entry level
- No Education
- Salary to negotiate
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 patternsDevelopment of end-to-end Credit models and credit policy for our existing credit productsLeverage alternate data to develop best-in-class underwriting modelsWorking on Big Data to develop risk analytical solutionsDevelopment of Fraud models and fraud rule engineCollaborate with various stakeholders (e.g.
tech, product) to understand and design best solutions which can be implementedWorking on cutting-edge techniques e.g.
machine learning and deep learning modelsExample 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 PythonFraud model development, deployment and rules for EMEA regionÂBasic 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 analysisExperience in at least one of the languages - R/Python/SAS and SQLExperience in in Credit industry (Fintech/bank)Familiarity with the best practices of Data ScienceÂAdd-on Skills :Â Experience in working with big dataSolid coding practicesPassion for building new tools/algorithmsExperience in developing Machine Learning models Skills:- Python, Data Analytics, R and R Programming
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