You will drive operational analytics across key risk areas including Fraud, Collections, Underwriting, and KYC Operations by turning complex business problems into scalable AI/ML solutions. By partnering closely with cross-functional stakeholders, you will ensure high-standard delivery and effective adoption of advanced analytical outputs to directly influence banking decisions, optimize modern workflows, and enhance customer communication strategy.
Responsibilities
- Analyze large volumes of structured and unstructured data to generate actionable insights across risk and operations.
- Apply advanced statistical techniques, predictive modeling, and AI/ML methods to develop practical solutions.
- Translate emerging business priorities into clearly defined analytics use cases with measurable outcomes.
- Manage end-to-end delivery of analytics initiatives from initial solution design to performance tracking.
- Collaborate with business, operations, and technology teams to implement production-ready AI solutions.
- Share knowledge and best practices to foster a collaborative and inclusive team environment.
- University degree in Statistics, Mathematics, Computer Science, Data Management, or a related discipline.
- Minimum of 6 years of experience in retail banking analytics, including predictive modeling and AI/ML application.
- Hands-on experience leveraging AI APIs, RAG pipelines, and AI coding assistants to automate analytics workflows.
- Advanced proficiency in Python, SQL (BigQuery), and Google Cloud Platform (GCP) for dataset optimization.
- Proven track record of building interactive, production-ready dashboards using Tableau or QlikSense.
- Strong stakeholder management and communication skills to clearly explain complex technical analysis to varied audiences.