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.