The role is responsible for leading large-scale analytics projects within the corporate banking space, focusing on Anti-Financial Crime (AFC) and Anti-Money Laundering (AML) initiatives. The candidate will analyze complex datasets, develop advanced models, and provide actionable insights to drive business impact and enhance risk management frameworks.
Key Responsibilities:
Analytics & Modelling
- Lead large-scale analytics projects targeting corporate clients to drive business impact in AFC/AML.
- Analyze structured and unstructured data to answer business questions through strategic analysis, machine learning, and natural language processing models.
- Develop, validate, and implement predictive and prescriptive models to support AFC/AML risk management and compliance initiatives.
Stakeholder Coordination
- Coordinate with internal teams and external partners to ensure smooth conversion of data into actionable insights.
- Ensure the successful implementation of insights and recommendations into business processes.
Business Impact & Advisory
- Provide data-driven recommendations to business units to enhance operational effectiveness and risk mitigation.
- Translate complex analytical findings into actionable strategies for senior management and stakeholders.
Requirements
- 710 years of experience in data analytics/science, with expertise in machine learning, natural language processing, and operations research.
- Hands-on experience with Python, R, SAS, Hadoop, Spark, or equivalent analytics tools.
- Strong problem-solving skills with solid understanding of financial industry operations.
- Consulting experience is a plus.
- Demonstrated sense of responsibility, teamwork, and ability to work in dynamic environments.
