Quikkloan - Data Scientist - Credit Risk Score Modeling

Key Responsibilities

- Use statistical modelling to develop an alternate credit model using traditional and non-traditional data (including social media and mobile & sms data) points model to the under-banked or thin file borrowers

- Use BIG Data, data mining, NLP/Text Mining,artificial intelligence / machine learning techniques to develop a standard statistical tool or custom underwriting algorithm

- Building ML based credit underwriting models, predictive models (Application Scorecard, Product, Loan Pricing, Loss Forecasting) Validation, deployment, and documentation of credit risk model

- Develop technical and functional designs for databases and score cards

- Integrate with various sources of data including Credit Bureau such as CIBIL Transunion, Experian, Equifax, CRIF Highmark, Government Data (UAIDAI Aadhar, Voters ID), Customer Financials (Bank Data), Demographics, Social Networks, Browser, and new data sources from diverse sources into credit decision making

Reporting - To Founder & CEO to identify, define and develop product requirement

Candidates Profile

Mandatory Skills - R, Python, SQL, Machine Learning

Mandatory Experience - 1 year of experience in building credit & application scorecard, predictive modelling role in Fintech/BFSI/financial service industry. The Candidate should have created at least 1-2 risk models and tested modelling output

Qualification - B.Tech (CS) / Master's in Economics/ Business/ Master's in Business Analytics with Quantitative & Statistics

Experience - At least 2-5 years of experience in credit risk modeling, scorecard development with a financial institution, credit bureau or fintech start-up.

Expertise - Knowledge of advanced analytics like predictive, forecasting, descriptive modelling, Machine Learning, deep learning