Data Scientist - Credit Risk Data - FinTech

Key Accountabilities:

• End-to-end risk model lifecycle management - develop, deploy, monitor.
• Data extraction using SQL / PySpark SQL; data cleaning and feature engineering.
• Model building using PySpark / Python on Spark.
• Proficiency in Logistic Regression, Random Forest, XGBoost, Markov Chain.
• Strategy performance tracking and swap-in / swap-out analysis.
• 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 to build/deploy the 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.

Mandatory Skills:

• Expertise in Big Data / ML: Build cutting-edge credit, churn, and usage models using advanced Machine Learning algorithms in a Big Data environment.
• Should have hands on experience and track record of delivering projects in individual capacity.
• Should be 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 analysing 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.
• Hands-on experience in credit, fraud, and churn model development & deployment.
• PD / EAD / LGD model development and validation.
• CSI / PSI model monitoring process experience.
• Track record of delivering projects independently.
• 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; ability to handle ambiguity and take calculated risks.

Desirable Skills:

• Business understanding of the fintech / consumer finance space.
• Experience in credit card or personal lending, especially in fintech.
• Hands-on experience working with Telecom data.