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.