LoanSimple - Credit Risk Modeling - Data Science

Credit Risk Modelling - Data Science

About Company :

Loan Simple is changing how business loans are given in India. In the current scenario, a majority of business loans are collateral-based loans, e.g. - Loans Against Property (LAP) or Gold loan. We are bringing the paradigm of short-term business finance as a pre-approved credit line, based on cash flows of a business.

We are giving loans based on POS (card swipe machines) transactions, and the aim is to move from credit under-writing based on POS to an automated credit model.

About Profile :

Credit risk modeling would be an integral part of Loan Simple, the objective is to develop an alternate credit model for different business verticals, and estimating their cash flow by taking into account non-traditional data points apart from relying on financial/regulatory statements provided by the business.

The key objectives of the function are:

- Building Predictive models (Application Score Card, Product, Loan Pricing, Loss Forecasting, Cross Sell Model)

-Develop and Maintaining Credit Risk Models & Strategies

- Creating Credit vision and Framework

- Identifying the opportunity area/segments where we can buy the risk and fulfill the lead

The function works directly with CXO's to identify areas of data analysis requirement, define problem statements and develop key insights.

Your skills and experience :

- 3 to 5 years of experience in leading teams to build an analytical solution for managing consumer credit risk with a financial institution, credit bureau or fintech startup.

- Strong experience in leading credit risk model development, validation, deployment, and documentation

Excellent Quantitative & Statistics background :

- Analytically oriented with ability to grasp complex risk management strategies, processes, models and draw insights / identify areas of opportunity

- Strong track record of delivering on high value / critical projects. Ability to communicate with senior stakeholders crisply and confidently on findings, status, bottlenecks, and escalations

- Ability to work independently, structure analyses and handle multiple priorities

- Proven track record of delivering in a start-up environment would be a plus

Academic Qualifications : B.Tech./ Master's in Economics/ Business/ Marketing Science/ Econometrics / Master's in business Analytics

Mandatory Experience: 3-5 year of experience in building Credit & Application Score Card, Predictive Modelling Role (Preferably in Fintech/BFSI/financial service industry)

Knowledge of: R, Python

Salary : As per industry standards, and we are open to offering Esops as potential hire would be one of the key employees in the company.