Data Scientist for Financial Inclusion
6 days ago
Company Overview
">We are a mission-driven team focused on driving financial inclusion to serve the underserved across their credit, savings and financial needs. Our goal is to create innovative solutions that bridge the gap between traditional banking and technology.
">About the Role
">This role is responsible for developing, monitoring and driving continuous enhancements to create best-in-class models/algorithms to assess risk, churn and uptake across the customer life cycle. You will work closely with our data engineering team to build and enhance the feature bank (foundational capability) to build/deploy various ML algorithms both for batch and real-time use cases.
">Key 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 various ML algorithms both for batch and real-time use cases
- Collaborate with credit policy/portfolio management team to drive P&L outcomes.
- Building reports for model monitoring and drive enhancements
Requirements
- Solid expertise in end-to-end risk model lifecycle management (develop, deploy, monitor)
- Previous hands-on experience in credit, fraud, churn model development and deployment
- Previous experience in 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;
- Strong entrepreneurial drive
Good to Have
- Good business understanding of the fintech/consumer finance space
- Experience in working with credit card/personal lending space, especially in fintech
- Hands-on experience in working with telecom data
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