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.