Vice President - Fraud Data Analytics, Group Compliance

Company: 1011 United Overseas Bank Ltd

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

The Compliance function is a strategic partner and a trusted business enabler to the Board and senior management. It is our responsibility to ensure that the Group continuously fulfils its regulatory obligations in today’s tight and dynamic regulatory landscape. To do that, we work closely with internal stakeholders to identify and to assess regulatory risks. This collaboration also includes developing practical solutions that integrate regulations into operational requirements as well as actively shaping and promoting stronger compliance culture and literacy in the Bank.

Job Responsibilities

Responsible for building UOB's Fraud analytical capabilities in response to external and internal requests; developing, maintaining, and upgrading in-house analytical models when needed

Support model maintenance

• Liaise with Business Analyst to receive and understand business feedback on model performance and incorporate feedback into models
• Re-train and recalibrate existing financial crime compliance analytical models to prevent model drift periodically or as needed

New model development

• Design and implement fraud detection models, rules, algorithms and dashboards using big data analytics tools such as Python, Hive, Spark, and Impala.
• Work closely with model end-users and other key stakeholders (e.g., Head of Compliance Analytics, Business Analyst, Data and Ops Engineer, GC) to identify additional areas which require analytics support or future model build and include those models in development pipeline
• Develop model narratives (e.g., purpose, logic, parameters, data requirements, output surfacing / structuring) in collaboration with the business and other relevant stakeholders
• Work closely with other Data Scientist(s) and Business Analyst, and undertake the end-to-end model development, including data wrangling, exploratory data analysis, feature selection, model selection, training, testing, etc.
• Build a range of models (rule-based, supervised / unsupervised models, etc.) on structured, semi-structured, and/or unstructured data if needed

Special projects

• Support special / high-priority projects, including building fraud analytical capabilities in response to external (e.g., regulatory) requests or internal intelligence, or based on gaps identified for existing analytical capabilities / models
• Keep abreast with the latest, cutting-edge developments in data science and advanced analytics and recommend adoption of best practices within the bank, in relation to Fraud and Financial Crime
• Communicate with Business Analyst to understand new regulatory requirements / policy updates relating to the areas / risks covered by the analytical models and work with the relevant teams to ensure that these updates are appropriately reflected in those models

Model governance

• Support the Head of analytics in identifying enhancements to existing model governance policies and processes, particularly in relation to newly built models
• Participate in the model governance process, including but not limited to model testing, assessing models for biases and for compliance with applicable ethics standards

SKILLS / QUALIFICATIONS

• 7 – 12 years of experience working in the technology space and preferably at least 3 - 5 years of data science / data analytics experience
• At least 2 - 3 years of experience working with advanced analytical models/tools/applications (e.g., machine learning)
• Prior experience working on large-scale analytics projects
• Experience in or familiarity with analytics related to Fraud / Financial Crime Compliance risks
• Monitor, analyze, and report on fraud-related data to drive continuous improvement in fraud detection and prevention efforts
• Ability to clearly communicate technical results in an easy-to understand manner and tailoring them to different audiences
• Ability to handle multiple priorities and work under pressure
• Bachelor's degree, or equivalent, in Computer Science, Engineering, Statistics, Mathematics, Business Analytics etc.

TECHNICAL SKILLS

• Python for data science, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
• Comfortable working with structured and unstructured data and distributed databases
• Familiar with natural language processing and network link analysis
• Familiar with best practice development standards

Additional Requirements

Develop, Engage, Execute, Strategise, University-Bachelor - Data Science & Analytics

Be 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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