Principal/Senior Data Scientist - Credit Risk Model (3-9 yrs)

The finance industry has ignored billions of deserving individuals. We are a mission driven team of finance, analytics and technology professionals, focused on driving financial inclusion to serve the underserved across their credit, savings and financial needs.

This role is responsible for development, monitoring and driving continuous enhancements to create best in Class models/algorithms to assess risk, churn and uptake across the customer life cycle

What we look for :

- Expertise in Big Data/ML : Should be able to build cutting edge credit/churn/usage models using advanced algorithms in a Big data/Machine Learning environment. Should have hands on experience and track record of delivering projects in individual capacity.

- Process oriented : Should help in building a process that maximizes operating efficiency while maintaining risk across multiple lending cycles. There needs to be an obsession with collecting and analyzing data to drive business iterations and improvements.

Willingness to go above and beyond : For start-ups the responsibilities and needs of the business change quickly. We're looking for someone who is not afraid to take on calculated risks and can deal with ambiguity.

Job Responsibilities :

- Own the end-to-end delivery of models/algorithms across customer life cycle; Develop innovative credit risk / churn / usage models using mobile wallet transaction data, Call data, Telecom usage data, customer bureau data etc

- Partner with the Data Engineering team to define the required data pipelines to build and enhance the feature bank (foundational capability) to build/deploy the various ML algorithms both for batch and real time use cases

- Collaborate with credit policy/portfolio mgmt. team to drive P&L outcomes.

- Building reports for model monitoring and drive enhancements

Required Qualifications & Skills :

- Solid expertise in end-to-end risk model lifecycle management (develop, deploy, monitor)

- Previous hands on in credit, fraud, churn model development and deployment

- Previous experience in Credit Risk - PD/EAD/LGD model development/validation

- Experience in CSI/PSI model monitoring process

- Hands on experience in data extraction using SQL/Pyspark SQL; data cleaning, feature creation and building models using Py Spark/Python on Spark; Scale will be a plus.

Previous exposure to below algorithms (preferably multiple) :

- Logistic Regression

- Random forest

- XGBOOST

- Markov Chain

- PSI/CSI for model monitoring

- Strategy performance tracking and swap in / swap out analysis

- Strong entrepreneurial drive