
VP, Compliance Analytics & Insights
- Singapore
- Permanent
- Full-time
- Assist the Team Lead in the development, implementation, and maintenance of next-generation Artificial Intelligence (AI) and Machine Learning (ML) AFC related models to mitigate financial crime risks using advanced analytics across the organization.
- Build and maintain predictive models, blockchain analytics, generative AI models, AI-driven behavioral analytics to identify financial crime risks.
- Develop model narratives (e.g., purpose, logic, parameters, data requirements, output surfacing / structuring) in collaboration with the business and other relevant stakeholders.
- Analyse transactional data to identify anomalies and patterns indicative of financial crime.
- Support the enhancement of existing monitoring systems and tools to improved detection efficiency and reduce false positives for the AFC surveillance models.
- Education: Bachelor’s degree in Data Science, Statistics, Finance, Business Administration, Computer Science, or a related field; Relevant professional certifications in AML, compliance, or data science is a plus.
- Experience: Minimum of 6-8 years in the financial services industry, including hands-on experience with AFC / sanctions analytics and compliance role. Proficiency in data analysis tools and software, such as SQL, R, Python, SAS or Network Link Analysis.
- Analytical Skills: Strong analytical, problem-solving, with the ability to think strategically and make data-driven decisions.
- AI/ML Knowledge: An understanding of AI/ML applications in compliance is a plus but not required.
- AML Knowledge: In-depth understanding of AML/CFT regulations, transaction monitoring systems, and anti-financial crime compliance best practices.
- Communication and Collaboration: Exceptional interpersonal and communication skills, with the ability to work across multiple departments and to drive discussions, manage and influence senior stakeholders.
- Soft Skills: Agile, inquisitive, self-driven, and capable of adapting to dynamic environments. Strong focus on integrity and meticulous attention to detail.
- Additional Preferences: Experience with big data analytics tools and frameworks, including Hive, Spark, and Impala, as well as Big data architecture and automation software tools