VP1, Data Analytics & Insights Specialist
Kuala Lumpur (City Area), Wilayah Persekutuan, MY, 50350
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. x 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.
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.
Job Responsibilities
OVERVIEW OF ROLE
Responsible for building analytical capabilities in response to external and internal requests; adopting in-house AFC analytical models into countries context. These includes driving and providing guidance to country AFC analytics team when engaging with the business, Group Compliance/AFC, regulators etc. to understand the needs and requirements and subsequently reflect these requirements in the AFC analytics models together with Group 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.
JOB RESPONSIBILITIES
- 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 re-train and recalibrate existing AFC analytical models to prevent model drift periodically or as needed.
- New model development
- Work closely with model end-users 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 Group modelling Data Scientist(s) and countries Business Analyst, and to support regional AFC model development for various 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 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, cutting-edge 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
- Model governance
- 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
- 5 – 10 years of experience working in the technology space and preferably 2 – 4 years of data science/data analytics experience
- 1 – 2 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 AML/AFC/compliance risks
- 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
- R and Python for data science, with strong 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
Be a part of 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.
Apply now and make a difference.
Competencies
1. Strategise2. Engage3. Execute4. Develop5. Skills6. Experience* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Business Analytics Computer Science Data Analytics Engineering Keras Machine Learning Mathematics ML models NLP Pandas Python R Scikit-learn Statistics TensorFlow Testing Unstructured data
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