Compliance Analytics - Phường Chí Minh, Hai Duong

Job summary

Compliance Analytics job at UOB involves creating, building, and maintaining data infrastructure and pipelines, supporting model development and deployment, and enhancing and supporting data quality. The role requires a bachelor's degree in Computer Science, Engineering, IT, Statistics, Mathematics, or Business Analytics, and 5-7 years of experience in technology and/or data analytics space.

Responsibilities

• Create, build, and maintain the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources.
• Deliver high-quality, production-ready data pipelines that bring and cleanse data from source systems to support AFC model build.
• Implement processes/systems to monitor data quality, and drive optimization, testing and tooling to improve data quality.
• Design and/or evaluates open source or vendor tools to be used for data lineage mapping.
• Make sure info/data flow from system to system is correct.

Requirements

• Bachelor's degree, or equivalent, Computer Science, Engineering, IT, Statistics, Mathematics, Business Analytics etc.
• The role is expected to have 5 - 7 years of experience working in technology and/or data analytics space, preferably 2 - 3 years of experience working in with advanced analytical models/tools/applications (e.g., machine learning, data-lake) in banking areas.
• Comfortable working with structured and unstructured data and distributed databases. Familiar with best practice development and validation standards
• Basic understanding and knowledge of banking, risk management, regulatory recommendations and industry standards related to AML/AFC/compliance risks. Experience in or familiarity with analytics related to AML/AFC/Compliance risks are advantages.
• Ability to clearly communicate complex results in an easy-to-understand manner and tailoring them to different audiences.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Experience in data engineering tools, schema design, dimensional data modelling, robotic process, natural language processing and network link analysis
• Strong communication skills to interact with data scientists, business end-users, and possibly external vendors to design and develop data solutions.

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