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Company Overview
A leading bank in Asia with a global network across 19 countries and territories, this organization operates through a strong presence in Singapore, China, Indonesia, Malaysia, and Thailand, as well as Europe and North America. With a history spanning over 80 years, the bank is guided by its core values—Honorable, Enterprising, United, and Committed—ensuring long-term success, integrity, and teamwork in all operations.
Job Description
The Data Analytics and Insights function manages multiple aspects of data management, business intelligence, analytics, governance, and quality. The VP of Regional Data Analytics & Validation is responsible for analyzing and reporting on complex datasets to evaluate, recommend, and support business strategies and operational processes. This role focuses on working with large-scale data to predict, improve, and measure key business outcomes, ensuring high-quality analytics in alignment with compliance requirements.
Job Summary
Build regional Anti-Financial Crime (AFC) analytical capabilities in response to internal and external requests.
Adapt in-house AFC analytical models for country-specific contexts.
Provide guidance to country AFC analytics teams when engaging with business units, Group Compliance/AFC, and regulators.
Conduct regular validation of AFC/AML models and manage internal and external stakeholder expectations.
Job Responsibilities
Report to Head, Regional Data Analytics Governance, overseeing DA development and support.
Collaborate with stakeholders to identify and assess data suitability for AFC models, ensuring datasets meet business requirements.
Design and implement advanced AML/Fraud detection models, rules, algorithms, and dashboards using big data tools such as Python, Hive, Spark, and Impala.
Contribute to model narratives by providing data-related insights, including requirements and availability.
Participate in testing models and outputs during development prior to formal validation by independent teams.
Create model deployment pipelines to automate model deployment in production environments, coordinating with Modelling teams, Group Technology, and Operations.
Ensure seamless deployment of new Anti-Financial Crime analytics solutions and models without unintended effects in production pipelines.
Job Qualifications
Bachelor’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, Economics, or related). Master’s degree preferred.
10–12 years of experience in data analytics, data science, or related fields, with 5–7 years working on advanced analytical models, tools, or applications (e.g., machine learning), preferably in financial services.
Proven track record in building and scaling analytics projects and ML/AI models across multiple geographies.
Expertise in data analytics methodologies, statistical modeling, machine learning techniques, and data visualization tools.
Proficiency in Python, R, SQL, and experience with big data technologies (Hadoop, Spark).
Experience with schema design and dimensional data modeling.
Strong analytical, problem-solving, and critical thinking skills; able to translate complex data into actionable insights.
Basic knowledge of regulatory recommendations and industry standards related to AML/AFC/compliance risks.
Experience or familiarity with analytics related to AML/AFC/compliance risks.
Ability to manage multiple priorities and work independently or in teams.
Excellent communication, interpersonal, and presentation skills; capable of influencing and engaging stakeholders at all levels and conveying complex results clearly to diverse audiences.
Disclaimer
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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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