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UOB

VP, Analytics Assurance, Grp Compliance

Reposted 3 Days Ago
Be an Early Applicant
In-Office
Singapore
Senior level
In-Office
Singapore
Senior level
The role involves validating Anti-Financial Crime models, reporting findings, collaborating with teams on model performance, and enhancing validation standards.
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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

Model validation

  • Independently validate Anti-Financial Crime (AFC) models in accordance with the bank’s model validation standards, producing comprehensive reports that document findings and actionable recommendations
  • Evaluate the robustness of model design, development methodology, and data integrity. Conduct thorough reviews of development code to ensure alignment with documented methodologies and results
  • Review and assess follow-up actions taken by model owners in response to issues identified in prior validations
  • Communicate validation outcomes clearly and effectively to management and stakeholders, translating technical findings in non-technical language
  • Collaborate with regional teams to prepare regular reports on model performance for senior management
  • Actively participate in the enhancement of model validation standards and frameworks

Team contributions

  • Stay informed on evolving regulatory requirements, industry best practices, and analytical advancements in AFC risk management. Propose updates to model development standards in consultation with the team lead
  • Assist in the planning and coordination of the model validation calendar
  • Support initiatives related to systems, infrastructure and databases used for analytic projects

Requirements

  • Undergraduate degree in a quantitative field, with 5 –8 years of experience in analytics / technology domain, and preferably 2 –3 years of experience in advanced data analytics
  • Prior experience working on large-scale analytics projects
  • Experience in or familiarity with analytics related to AFC/AML/compliance risks
  • Strong ability to communicate complex technical findings clearly and effectively, tailored to both technical and non-technical audiences
  • Demonstrated capability to manage multiple concurrent projects in a fast-paced environment

Technical skills

  • Proficiency in Python and / or R for data science, with practical knowledge of data wrangling and machine learning libraries (e.g., Pandas, Keras, Tensorflow, Sklearn)
  • Proficiency in querying and visualization tools such as SQL and Qlik will be an advantage
  • Comfortable working with structured and unstructured data and distributed databases
  • Familiar with natural language processing and network link analysis
  • Familiar with model development and validation best practices

Additional Requirements

Develop, Engage, Execute, Strategise

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.

Apply now and make a Difference

Top Skills

Keras
Pandas
Python
Qlik
R
Sklearn
SQL
TensorFlow
HQ

UOB Singapore Office

80 Raffles Place, Singapore, 048624

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