Senior Data Scientist

Job Description for Principal/Sr Data Scientist

• 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

• 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.

• 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

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

1. Previous hands on in credit, fraud, churn model development and deployment
2. Previous experience in PD/EAD/LGD model development/validation
3. 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
• Good to have:
• Good business understanding of the fintech/consumer finance space
• Experience in working with credit card / personal lending space, esp fintech
• hands on experience in working with Telecom data