- Location
- Central Region (City Area), Singapore
- Workplace
- Onsite
- Type
- Full-time
- Department
- Legal
- Seniority
- VP
- Experience
- 12+ years
- Education
- Master
- Source
- Workday
Description
About UOB
United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.
Job Description
Compliance Analytics and Modelling is responsible for ensuring that all activities comply with regulatory requirements, including financial crime, anti-money laundering, anti-bribery and corruption, data privacy, and sanctions. The Analytics, Modeling, & Reporting area is responsible for analyzing and reporting on data sets for a particular area to evaluate, recommend and support the implementation of business strategies and operational processes.
Job Responsibilities
Responsibilities and Activities
- Data Science & AI Strategy: Develop and execute the data science and AI/ML strategy for Integrated Surveillance, aligned to financial crime risk priorities, regulatory expectations and business objectives.
- Unified Surveillance Analytics: Design and deliver risk signals, analytical features and detection models across AML, sanctions, fraud, scams and other financial crime domains.
- Model Development: Lead the end-to-end development of analytical solutions, including data exploration, feature engineering, model development, testing, validation and deployment.
- Risk Signals & Feature Management: Establish reusable risk indicators, features and analytical assets to support surveillance, investigations and downstream platforms.
- Model Governance: Ensure robust model governance, documentation, explainability, monitoring and performance management throughout the model lifecycle.
- Innovation & Emerging Risks: Leverage AI, machine learning and advanced analytics techniques to address emerging financial crime risks and enhance surveillance effectiveness.
- Data & Technology Collaboration: Partner with data engineering and technology teams to define data requirements, optimize data assets and enable scalable analytical solutions.
- Stakeholder Engagement: Work closely with Compliance, Financial Crime Compliance, Operations and business stakeholders to identify opportunities and deliver impactful analytics solutions.
- Operationalisation & Value Realisation: Drive production implementation, adoption and continuous improvement of analytical capabilities through effective monitoring and feedback mechanisms.
- Leadership & Capability Building: Provide technical leadership, mentor team members and promote best practices in data science, AI and analytics across the Integrated Surveillance function.
Job Requirements
Skills / Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, Finance or a related discipline; Master's degree or relevant professional certifications are advantageous.
- Minimum 12 years of experience in financial services, with at least 8 years in financial crime analytics, surveillance, AML, sanctions, fraud or risk management.
- Proven experience in developing and implementing large-scale analytics, AI/ML or financial crime surveillance solutions.
- Strong understanding of model governance, model risk management and regulatory expectations across the model lifecycle.
- Experience leading strategic initiatives, large-scale transformation programmes and operating model development.
- Strong knowledge of financial crime typologies, regulatory requirements, industry best practices and emerging risk trends.
- Excellent analytical, problem-solving and decision-making capabilities with a data-driven mindset.
- Proficiency in Python, SQL and analytical tools; experience in machine learning, graph analytics, network analysis or GenAI applications is advantageous.
- Experience with big data platforms and technologies, including Hive, Spark, Impala and cloud-based analytics environments.
- Familiarity with AI/ML model development, feature engineering, model monitoring, explainability and responsible AI practices.
- Demonstrated leadership, stakeholder management and team development capabilities.
- Strong communication and interpersonal skills, with the ability to translate complex analytical concepts into business outcomes.
- Ability to manage multiple priorities and deliver results in a fast-paced, cross-functional environment.
Additional Requirements
Develop, Engage, Execute, StrategiseBe a Part of the UOB Family
UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.
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