Fvp/svp, Regional Data Analytics, Group Compliance
2 weeks ago
Posting Date: 09-Feb-2023
Location:
Singapore, Singapore, Singapore
Company:
United Overseas Bank Ltd
About UOB
About the Department
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.
Responsibilities:
Responsible for building Regional AFC analytical capabilities in response to external and internal requests; adopting in-house AFC analytical models into countries context.
to understand the needs and requirements ad subsequently reflect these requirements in the AFC analytics models together with Group Modelling team/ Centralised Modelling Team.
This role also need to ensure that the design and data architecture for the countries supported can support AFC analytics needs so that we can have a seamless deployment of AFC analytical models into production environment and compatibilities of country specific systems against the model to be deployed.
Support model maintenance- Liaise with countries Business Analyst to receive and understand business feedback on model performance and incorporate feedback into models' enhancement/ maintenance.
- Together with country data analytics team and centralized modelling team perform retrain and recalibrate existing AFC analytical models to prevent model drift periodically or as needed.
- Work closely with model endusers and other key stakeholders (e.g., Head of Modelling, 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 in respective countries.
- Work closely with centralized modelling Data Scientist(s) and countries Business Analyst, and to support regional AFC model development for various range of models (rulebased, supervised/unsupervised models, etc.) on structured, semistructured, and/or unstructured data if needed
- Support special/highpriority projects, including building AFC 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, cuttingedge developments in data science and advanced analytics and recommend adoption of best practices within the bank, in relation to AFC/AML
- Communicate with countries Business Analyst to understand new regulatory requirements/policy updates relating to the areas/risks covered by the AFC analytical models and work with the relevant teams to ensure that these updates are appropriately reflected in those models
- Support the Head of Analytics Assurance 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
Job Requirements
years of experience working in the technology space and preferably 2 -4 years of data science/data analytics experience
- Prior experience working on largescale analytics projects
- Experience in or familiarity with analytics related to AML/AFC/compliance risks
- Ability to clearly communicate technical results in an easytounderstand 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
- R and 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
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