Data Scientist for Financial Inclusion

3 weeks ago


Gurgaon, Haryana, India Yabx Full time

At Yabx, 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. We have ignored billions of deserving individuals in the finance industry.

Job Summary

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. The successful candidate will be an expert in Big Data/ML with hands-on experience in building cutting-edge credit/churn/usage models using advanced algorithms in a Big data/Machine Learning environment.

We are looking for someone who is process-oriented and can help build 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.

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 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
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; 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
Benefits

Our estimated salary for this role is between $120,000 - $180,000 per year. This estimate is based on national averages for a Senior Data Scientist position in the United States. However, please note that salaries may vary depending on location, experience, and other factors.


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